Review of General Psychology Copyright 1997 by the Educational Publishing Foundation 1997, Vol. 1, No. 1,42-71 1089-2680/97/$3.00

Complex Adaptive Systems in the Behavioral and Social Sciences

Roy J. Eidelson Bala Cynwyd, Pennsylvania

This article examines applications of complexity theory within the behavioral and social sciences. Specific attention is given to the fundamental characteristics of complex adaptive systems (CAS)--such as individuals, groups, and societies-- including the underlying structure of CAS, the internal dynamics of evolving CAS, and how CAS respond to their environment. Examples drawn from psychology, sociology, economics, and political science include attitude formation, majority-minority rela- tions, social networks, family systems, psychotherapy, norm formation, organizational development, coalition formation, economic instabilities, urban development, the electoral process, political transitions, international relations, social movements, drug policy, and criminal behavior. The discussion also addresses the obstacles to implement- ing the CAS perspective in the behavioral and social sciences and implications for research methodology.

Over the past decade, investigators in many formation, majority-minority relations, social fields have increasingly directed their attention networks, family systems, psychotherapy, norm toward the dynamic processes and global formation, organizational development, coali- pattems that emerge from the collective interac- tion formation, economic instabilities, urban tions of a system's individual components (e.g., development, the electoral process, political Cowan, Pines, & Meltzer, 1994; Holland, 1995). transitions, intemational relations, social move- Using theoretical models and research strategies ments, drug policy, and criminal behavior. that focus on nonlinear effects and temporal But despite the enthusiasm of its interdisciplin- change, complexity theory researchers have ary proponents, the study of nonlinear dynami- discovered that a system's evolution and behav- cal systems has thus far failed to generate ior often defy many commonly held assump- widespread interest and application within the tions about the world. For example, their community of behavioral and social scientists. A findings reveal that randomness and determin- number of interrelated factors have contributed ism often coexist, that the whole cannot always to this situation. First, there is currently much be understood by reducing it to simpler parts, confusion over the concepts and definitions that instability is commonplace, and that change central to this relatively new area of scientific is frequently abrupt and discontinuous (e.g., inquiry. The term complexity itself is burdened Casti, 1994). with a multitude of different technical meanings, Although most of the principles of complex- including the amount of thermodynamic entropy ity theory have originated in the physical and in a system, the degree to which information is natural sciences, Gell-Mann (1995) is among shared by a system's components, and the those who see the potential for a much broader diversity displayed by the hierarchical levels of impact: "Even more exciting is the possibility a system (Horgan, 1995). When researchers in of useful contributions to the life sciences, the diverse fields use their own particular transla- social and behavioral sciences, and even matters tions of fundamental terminology, the resultant of policy for human society" (p. 322). Indeed, "interdisciplinary Tower of Babel" (Scott, many areas of the behavioral and social sciences 1991) serves only to further muddy the scientific have already attracted the attention of complex- waters. Vague distinctions between rigorous and ity investigators; among these fields are attitude metaphorical implementations, such as with the notion of chaos, also beset complexity theory at Correspondence concerning this article should be ad- the present time (e.g., Abraham, 1995; Barton, dressed to Roy J. Eidelson, 413 Pembroke Road, Bala 1994). Cynwyd, Pennsylvania 19004. Certain basic assumptions in the social sci- 42 COMPLEX ADAPTIVE SYSTEMS 43 ences create another obstacle to broader applica- well serve to establish the groundwork for such tion of complexity models in these disciplines. an undertaking. As a contribution to the process, Heylighen and Campbell (1995) have termed this paper offers an overview of one particular one of these assumptions methodological indi- arena in the realm of complexity theory-- vidualism, which they described as the view that complex adaptive systems (CAS). Throughout "all social processes are to be explained by laws the discussion that follows, links are made of individual behavior, that social systems have between key concepts and theoretical and no separate ontological reality, and that all empirical work by investigators in the fields of references to social systems are merely conve- psychology, sociology, economics, and political nient summaries for patterns of individual science. behavior" (p. 2). Similarly, Leydesdorff (1993) What, then, is a complex adaptive system? noted that in most approaches to modern Most generally, a CAS is a large collection of sociology "social change has to be explained in diverse parts interconnected in a hierarchical terms of, or at least with reference to, individual manner such that organization persists or grows human impact" (p. 331). In sharp contrast, over time without centralized control. The brain Cowan (1994) raised the possibility that "soci- (e.g., Haken, 1996; Kelso, 1995), the immune etal behavior cannot be adequately described by system (e.g., Bremermann, 1994; Holland, any practically achievable integration across the 1995; Varela, Sanchez-Leighton, & Coutinho, behavior of individuals" (p. 4). 1992), an ant colony (e.g., Kelly, 1994; Sole, A second pervasive assumption in the behav- Miramontes, & Goodwin, 1993), and human ioral and social sciences is that human systems society (e.g., Mainzer, 1993; Weidlich & Haag, are driven toward a stable equilibrium, and that 1983) are often presented as examples. only one such equilibrium-state exists for a Through a dynamical, continuously unfolding given system. The presence of unstable dynam- process, individual units within the system ics is interpreted as being a consequence of actively (but imperfectly) gather information "social disorganization, faulty design, malfunc- from neighboring units and from the external tioning or deviancy" (Young, 1991, p. 292). environment. This information is subjected to Such a perspective inevitably minimizes the local internal rules, and responses are formu- recognition of and significance accorded to lated; these responses then work their way self-organized, far-from-equilibrium dynamical through the web of interconnected components. systems--the very heart of the complex-systems Within the CAS, competition operates to main- perspective. tain or strengthen certain properties while It is not surprising that efforts to adopt a new constraining or eliminating others. Entirely new paradigm for studying individuals and societies, properties can also emerge spontaneously and such as that provided by complexity theory, unexpectedly. Configured in this manner, the have met with resistance (e.g., Kuhn, 1970). complex adaptive system is poised for potential Such conflict, however, can ultimately prove change and adaptation either through alteration constructive. As Kac (1969) noted, the main role of its rules, connections, and responses or of competing models is twofold--to polarize through modification of the external environ- thinking and to pose sharp questions. However, ment. In fact, the external stimulus impacting a because there is not yet a "unified theory of CAS is often one or more other complex complex systems" (Horgan, 1995), there ap- adaptive systems. The resulting coevolution is pears to be the predictable polarization of sides, itself an extremely complicated process. but not an organized set of definitive, testable Given the breadth of the topic, the framework propositions for researchers to evaluate. for this paper is necessarily arbitrary and At this point, then, it is important for experts incomplete. Nevertheless, four important sub- in the behavioral and social science disciplines ject areas have been selected for particular without allegiance to complexity theory to give attention: (a) the principles underlying the careful consideration to this growing field and structure of complex adaptive systems; that is, determine whether and where its perspective how CAS are put together; (b) the evolution of may be useful for them. Such a step is clearly CAS over time, with a focus on self- more modest than constructing (or evaluating) a organization and non-linear change; (c) the unified theory of complex systems, but it may relationship between the complex adaptive 44 EIDELSON system and its environment, including adapta- tion of any overarching organization (Tryon, tion and coevolution; and (d) an analysis of the 1995). theoretical and empirical issues central to Freeman's (1991, 1995) neurophysiology re- effectively evaluating or implementing the CAS search offers intriguing evidence that the brain paradigm in the behavioral and social sciences. itself from which neural networks derive their inspiration---demonstrates distributed control. Whereas the individual neuron's membrane The Underlying Structure of CAS provides it with considerable local autonomy, Hierarchical Arrangements With each neuron's activity impacts the other neurons Distributed Control in its vicinity. These interactive masses are simultaneously and reciprocally linked to other The numerous and diverse interacting units local and more distant neural masses. As an that constitute a complex adaptive system are example, Freeman reports data indicating that typically arranged in a hierarchical structure. every neuron in a rat's olfactory bulb responds Simon (1995) described the arrangement as to the stimulation provided by a discriminable "sets of boxes nesting within sets of boxes" odor. He concludes that "the neural information (1995, p. 26) through several repetitions. that correlates with the behavior of animals Similarly, Holland (1995) has explained that exists in the cooperative activity of many new hierarchical levels are created whenever millions of neurons and not in the favored few" individual units, or agents, are aggregated. (1995, p. 22). Indeed, he views this process of aggregation as Social systems also demonstrate decentral- one of the most basic elements of complex ized control in a variety of ways. In animals, for adaptive systems. In turn, each aggregate can example, the "intelligent" behavior of a swarm connect with other aggregates to form meta- of bees selecting a new hive site or a colony of agents, which can then combine to form ants locating a food source unfolds despite the meta-metaagents, and so on. In this way, the absence of an executive agent (Kelly, 1994). aggregation of business finns forms an economy, Similarly, Huberman and Hogg (1995) have the combination of antibodies creates an im- observed that communities of practice-- mune system, and a network of neurons forms informal networks of people ranging from the nervous system. Simon (1995) has noted, chemists in competing pharmaceutical firms to however, that some aggregations, such as the foreign affairs personnel of adversarial human society, involve an especially complex countries to gangs in schools and prisons-- network structure because each agent may develop interaction structures that do not rely on belong within a number of different boxes at the central controls. Indeed, the investigators' math- same hierarchical level (e.g., an individual may ematical models indicate that dynamical instabili- simultaneously be a member of a family, a ties in these interaction patterns often produce professional organization, and a therapy group). spontaneous adaptive realignments among the Each component part in the CAS is relatively members without the intervention of a central autonomous in function and generally capable planner. of individualized responses to local events (e.g., Regarding human society more broadly, Holland, 1992, 1994; Kelly, 1994; Langton, Brown (1995) has analyzed the social conven- 1995). This phenomenon is illustrated, for tions that frequently become powerful influ- example, in the connectionism of neural net- ences on behavior. Forming lines at a banking works (parallel distributed processing systems machine or a fast-food drive-through window with applications ranging from financial-market and the unplanned coordinated activity of prediction to patient classification). Rather than strangers confronted with an emergency situa- relying on a central processing unit as most tion are instances of organization dependent on supercomputers do, input information in a distributed control. In a like manner, Axelrod neural network is only exchanged locally among (1986) has concluded that norms often serve as neighboring nodes. Through summation pro- mechanisms to coordinate behaviors and regu- cesses based on nonlinear threshold functions, late conflicts without the intervention of a the actions of interacting components produce central authority. He has pointed out that the network's response even without the imposi- societal norms in fact often precede the COMPLEX ADAPTIVE SYSTEMS 45 formulation or enactment of laws. Interestingly, villagers; she stresses that the dam was economi- in computer simulations of the evolution of cally pointless because there simply were no norms under conditions of limited rationality, solvent city markets or industries to use its Axelrod found that metanorms, such as the power. expectation that an individual will punish It is important to note, however, that the someone who fails to punish a norm-violator, distributed control of CAS is not without its can play important roles in establishing and potential drawbacks. Hardin's (1968) "tragedy protecting group norms. of the commons" describes one of them very When efforts are made to impose some degree effectively. Imagine a situation in which a of centralized control on social, political, and common resource (e.g., land for grazing cattle) economic systems, the outcomes are often is available for shared use by all members of a disappointing and unanticipated. Heylighen and community (e.g., a group of herdsmen). As each Campbell (1995), for example, have cited two individual increasingly uses the commons in an reasons why consolidating the control of an effort to maximize his own benefit, the collec- organization in a subgroup or individual can be tive consequence may well be the destruction of problematic. First, important knowledge is the resource from excessive exploitation. In likely to be farther removed from the local site short, localizing control at the level of each or situation where it is most needed. Second, the agent or component can prove catastrophic if transfer of information in both directions--is competing demands go unrecognized or unre- highly susceptible to delays and degradation. solved. More speculatively, multiple personality Furthermore, they noted that "the capacity of disorder may be an even more striking instance the control system for anticipation, which in which distributed control, in this case within normally compensates for the loss of informa- the human brain, produces extraordinary out- tion, is notably poor for social systems, which comes (e.g., Putnam, 1989). are inherently difficult to predict" (p. 16). Goerner (1994) has echoed these admonitions, Interconnections Among CAS Components and emphasized that dominator hierarchies, characterized by the upward flow of information Another important structural feature of a and the downward exercise of control, can stifle complex adaptive system is the nature of the creativity and the development of greater connections among its components. Simon efficiencies. (1981) described the typical configuration as Jacobs' (1984) analysis of the problems "near decomposability." That is, intracompo- encountered by large nation-states governing nent linkages tend to be stronger than intercom- their cities through centralized control and ponent linkages, and neighboring components centralized problem-solving also supports these tend to have stronger connections than distant conclusions. In particular, she argued that components. Huberman (1992) explained that "national or imperial currencies give faulty and this method of organization allows for "an destructive feedback to city economies and that effective isolation of a given level from both the this in turn leads to profound structural eco- rapid fluctuations of the lower echelons and the nomic flaws, some of which cannot be overcome quasi-static constraints of the higher ones" no matter how hard we try" (p. 158). Jacobs has (p. 129). suggested that broad national economic policies Both the absolute number of connections are flawed because they ignore the unique between units and the strength (or frequency) of features and needs of individual cities and these linkages can play consequential roles. thereby interfere with locally informed efforts at Kelly (1994) has speculated that in nature self-correction and stable growth. She has connectance is conserved by a trade-off between compared this common circumstance to an these two particular measures; changes in one imaginary one in which an elephant, three dimension will likely lead to compensating sheep, two puppy dogs, and a rabbit are all changes in the other. Similarly, interaction connected to the same brain-stem breathing patterns among members of an organization, center--not all are likely to survive. Among the such as coworkers, typically range from infre- real-life examples Jacobs has provided is the quent contacts with all fellow members to very Volta Dam in Ghana, which displaced 80,000 frequent contacts with just a few colleagues 46 EIDELSON

(Huberman & Hogg, 1995). Adding the dimen- areas suggesting that adding members to a sion of linkage quality in his discussion of social system can prove costly. Based on computer systems, Merry (1995) also has emphasized the simulations of information-processing organiza- importance of matching the degree of interdepen- tions, Miller (1995) has noted that additional dence among individuals with the quality of nodes (e.g., workers) can be a mixed blessing. their relationships. He has hypothesized, for Although they may potentially increase the example, that when interdependence is high and organization's processing power, they also relationship quality is low, the participants (e.g., extend and elaborate the pathways through work-team members or nations) are likely to which the information must flow. Similarly, in endure an uncertain period of conflict and crisis. an exploration of simulated ecosystems, May A related issue is whether there is an ideal (1973) found that combining too many different level of connectivity within a CAS. On the one species tended to destabilize the system and hand, inadequate connections can make it produce higher extinction rates. Interestingly, difficult for the system to coordinate adaptive May hypothesizes that diversity and stability responses to internal or external changes. For can perhaps coexist most comfortably when example, if messages fail to reach their targeted subsystems develop to control cross-species destinations in a timely manner, disruptive interaction (i.e., by limiting connections per influences may attain a secure foothold before species). countervailing forces can be activated. In this Excessive numbers can also prove to be a regard, Varela (1995; Varela, Sanchez-Leighton, liability when a group is faced with a social & Coutinho, 1992) has proposed that both dilemma requiting collective action (e.g., envi- autoimmune diseases and drug addiciton are ronmental protection). Computer simulations disturbances caused by insufficient connected- reveal that overall cooperation tends to be ness throughout the afflicted system. From his unsustainable when group size exceeds a critical perspective, in the first instance the body's threshold (Glance & Huberman, 1994; Huber- immune system suffers from inadequate internal man & Glance, 1993). As the authors explained, regulation, causing vaccination to be ineffective beyond that threshold "the likelihood of bad as a treatment; in the second case, healthy consequences from an individual's defection connections between the addicts and the larger becomes so small, whereas the potential gain society have been severed. stays so large, that the disincentive to defect Other investigators, however, have discov- vanishes" (Glance & Huberman, 1994, p. 78). ered that excessive connectivity can also endan- They noted, however, that creating subsystems ger a system. Kauffman (1993) investigated this within an organization may produce "pockets of phenomenon using randomly assembled Bool- collaboration" that can spread throughout the ean networks in his computer simulations of entire system. genetic systems. In such arrangements, each element's current binary "on/off'' state is Flexibility, Redundancy, and Error regulated by its logical switching rule and the Management states of specific neighboring elements at the preceding time interval. For example, a particu- Within a complex adaptive system, the lar node may be on only if all surrounding nodes weblike network of interconnections can also were previously off. Kauffman discovered that enhance error management capabilities. In this his networks suffered paralysis when the num- regard, von Neumann (1966) observed that the ber of connections per node exceeded a structures of both natural and human-made threshold value, which suggests that an indi- automata are greatly influenced by the precau- vidual component of a CAS may simply be tionary arrangements designed to minimize the unable to devise an adaptive response when likelihood that any failure will prove lethal. The faced with an overload of conflicting inputs. CAS typically limits system-threatening mis- In reviewing Kauffman's findings, Kelly takes in several ways. First, its hierarchical (1994) concluded that system evolution can "boxes-in-boxes" structure often confines the proceed most rapidly by adding members while tipples caused by any single error. Second, an holding the average number of links per node elaborate network of feedback loops reduces the constant. However, there is evidence from other likelihood of a similar mistake being repeated. COMPLEX ADAPTIVE SYSTEMS 47

And third, the system incorporates a significant ibility inherent in a system composed of many degree of redundancy in its components so that smaller, independently functional units. Kelly "replacement" parts or pathways are frequently (1994) has advised, however, that the network available when a failure does occur (e.g., Kelly, structure of a CAS also places constraints on its 1994). malleability and the range of adaptations In examining this last phenomenon, Minsky accessible to it. The CAS can change only by (1986, 1995; Minsky & Papert, 1987) has means of a step-by-step process operating explored how a person learns which methods are through its component parts; modification of generally most effective for solving particular these parts, in turn, is limited by the structure of problems. He has stressed that people are more their own subcomponents, and so on. As a result, adaptable than computers because in fact they change occurs in discontinuous steps rather than usually know several ways to accomplish the continuously. Goodwin (1994a, 1994b) has same thing. Whereas the typical computer described similar limitations when discussing program is paralyzed by any error of any size, the contrasting roles of natural selection and the brain almost always finds some alternative morphogenesis in the evolution of species. method to tackle a problem when one particular Although natural selection may underlie the approach has proven fruitless. By continuously persistence of particular forms, it does not aid in devising new, seemingly redundant ways to our understanding of why these forms ever accomplish currently manageable tasks a person existed in the first place. Goodwin has stressed is better prepared if or when the old ways cease that issues of morphology alone place signifi- to work. Indeed, Minsky (1995) described the cant limitations on possible biological forms, human brain as, basically, a "collection of long before survival of the fittest enters into the kludges" (p. 158) in which bits of machinery are equation. In short, some complex systems may added whenever necessary to meet a specific not exist in a particular form because the parts need without an underlying global plan. He simply cannot be assembled that way. suggested that, instead of having a few underly- ing basic principles, the brain is "a great The Internal Dynamics of the Evolving jury-rigged combination of many gadgets to do CAS different things, with additional gadgets to correct their deficiencies, and yet more accesso- Self-Organization ries to intercept their various bugs and undesir- able interactions" (p. 159). A hallmark of complex adaptive systems is Similarly, Holland (1994) has explained that their capacity for self-organization. Barton if one of the components of a CAS is removed or (1994) describes self-organization as "a process disabled, the others often successfully reorga- by which a structure or pattern emerges in an nize themselves and compensate for the loss open system without specifications from the with changes that may even create niches where outside environment" (p. 7). Similarly, Farmer none had previously existed. In this regard, (1995) depicts self-organization as the way CAS Kelso (1995) has reported experimental evi- "naturally progress from chaotic, disorganized, dence that a variety of human behavior patterns undifferentiated, independent states to orga- reveal "invariance of function" even when key nized, highly differentiated, and highly interde- connections among component parts are recon- pendent states" (p. 368). Central to the phenom- figured. As a specific instance, he and his enon is the interplay between constancy and colleagues (Kelso, Tuller, Vatikiotis-Bateson, & change as the system maintains its essential Fowler, 1984) devised a prosthesis so that they identity while undergoing self-induced, nonlin- could instantaneously perturb a volunteer's jaw ear transformations. movements during speech. They discovered Many of the major principles of self- that, without any practice whatsoever, the organization have emerged from Prigogine's participant's lips or tongue would spontaneously work on far-from-equilibrium thermodynamics compensate when the jaw was suddently dis- (e.g., Nicolis & Prigogine, 1977; Prigogine & abled and thereby enable the vocalization of the Stengers, 1984) and from Haken's theory of intended sounds. synergetics (e.g., Haken, 1983a, 1983b, 1988). Such findings highlight the remarkable flex- According to the latter's perspective, the coUec- 48 EIDELSON tive interactions among a system's individual discovered that patterns of segregation emerged components produce macroscopic properties that frequently overstated the actual minimal referred to as order parameters. These order preferences of the individuals involved. That is, parameters, such as the roll patterns of fluids and even a limited desire to avoid being part of a the light waves of lasers, thereafter "enslave" small minority tended to alter a reasonably well the actions of the elementary units in a top-down integrated neighborhood and create a highly manner. At the same time, the constituent parts segregated one instead. continue to operate in a bottom-up fashion to Latane and his colleagues have examined support and reinforce the order parameters. similar emergent phenomena in the processes Once established, this pattern of circular causal- underlying group attitude change (e.g., Nowak, ity serves to stabilize the CAS, unless perturbed Szamrej, & Latane, 1990). Based on the view by external influences. that important attitudes act as categories rather Order parameters have been used to describe than dimensions (Latane & Nowak, 1994), the important features of a variety of CAS in the Latane, Nowak, and Liu (1994) designed behavioral and social sciences. In regard to computer simulations in which each agent human cognition, for example, Stadler and maintained an opinion as long as the balance of Kruse (1995) have identified meaning as an social influence pressures from other agents did order parameter for high-level brain processes; not favor the opposing point of view. In such a in many experiments, meaning serves as the model, the combined pressures to switch opin- organizational basis for the memory of complex ions and pressures to stay with one's opinion verbal chains. Within the economic realm, a (which include the strength of the agent's own business firm's profits can act as an order opinion) are nonlinear in their impact; incremen- parameter for the company's diverse activities; tal changes in influence produce no effect until in the larger society, the difference in the they reach a sufficient level, at which point the number of citizens supporting two opposing individual reverses his or her position. solutions can operate as an order parameter for Using a square grid in which each randomly the community's response to an important assigned cell corresponded to an individual with problem (Wishcert & Wunderlin, 1993). Finally, either of two opposing attitudes, Latane, Nowak, Haken (1993, 1994) speculates that all of the and Liu (1994) found that over time the following can emerge as order parameters simulations produced significant changes from within a particular CAS: language, national the initial configurations in reference to two character, ritual, form of government, public order parameters. In regard to the first param- opinion, corporate identity, and social climate. eter-the polarization of opinions--incomplete Using simulation techniques, investigators polarization emerged; that is, the number of have documented self-organizing transforma- minority-view members diminished but did not tions across a broad spectrum of social and disappear entirely. As for the second global economic systems. Schelling (1978), for ex- variable--the clustering of opinions---cluster- ample, developed a self-forming neighborhood ing increased so that agents with shared model to explain the collective impact of opinions became more spatially segregated from individual preferences in regard to community those with the opposing viewpoint. Latane and racial composition. He devised a hypothetical Nowak (1994) describe the resulting self- checkerboard neighborhood in which each organized equilibrium as one of "clustered resident was assigned to a square, and his or her groups in which minority members are shielded degree of discontent was based solely on the from the prevailing majority influence, finding number of same-colored versus different- themselves in local neighborhoods wherein their colored neighbors occupying the immediately view is in the majority" (p. 244). They further adjacent squares. Importantly, whenever a per- suggest that strong-willed people around the son moved from a current site to a vacant edge of a minority-cluster (i.e., those least likely square, the color ratios were altered in both the to change to the majority viewpoint) can enable abandoned neighborhood and the new one. As the less committed within to actually believe each resident sought out a square of content- they are part of a majority. ment, individual actions combined to create As another example, Glance and Huberman global patterns. In these simulations, Schelling (1994) examined how and whether group COMPLEX ADAPTIVE SYSTEMS 49 cooperation arises in situations requiring collec- world). It should be kept in mind, however, that tive action. They discovered that their systems successful self-organization for a particular tended to evolve toward either of two stable but system as a whole can produce undesirable contrasting conditions: widespread defection consequences for some of its individual parts among the agents or widespread cooperation. and for other CAS. Regardless of where the group started, random A common instance of positive feedback is perturbations caused by the agents' uncertainties the competency trap (March, 1994). In this regarding each other's behaviors and inclina- particular situation, successful learning drives tions eventually caused the system to move an individual, organization, or society to a stable rapidly to the more stable of these two states. but suboptimal solution. For example, once an Glance and Huberman have interpreted their individual has developed a skill and derived findings as indicating that a cooperative resolu- positive outcomes from its use, he or she will tion is most likely when a particular social group have little incentive to learn an alternative is relatively small, hetergeneous, and focuses on method, even if it would potentially provide long-term consequences. superior returns. Such a change not only would Self-organizing patterns in the economic entail the costs in time and energy of learning a arena have also been investigated (e.g., Allen, new approach, but could also expose the person 1982; Krugman, 1994). Allen (1982), for to a diminished success rate until proficiency example, analyzed the evolution of urban improves. Furthermore, with each successful centers. The decision an individual, family, or implementation of the old skill, the reinforce- business makes in selecting a home site is ment increases the disincentive to switch. influenced by a multitude of interacting, nonlin- Arthur's (1988, 1990) analysis of increasing ear factors. These include the availability and returns (i.e., positive feedback) in economic quality of local employment and housing, and systems is also instructive. Conventional eco- the competing opportunities offered by neighbor- nomic theory emphasizes the role of diminish- ing communities. Such selections need not be ing returns (negative feedback) in establishing a permanent. Depending on the relative costs single and best equilibrium for prices and involved, agents may choose to relocate as market shares. Arthur has pointed out, however, circumstances change with the passage of time. that there are many parts of the economy, The collective impact of many such individual especially those driven by technological innova- decisions became apparent in Allen's computer tion, in which positive feedback dominates. In simulations. Over time an urbanization process these situations, expensive initial investments in unfolded as an initial network of equally research and design are typically followed by populated cells transformed itself into a geo- relatively low incremental production costs. graphical space with a few high-density centers When companies compete in such an arena, an surrounded by satellite cities and more distant early sales lead--even if caused by nothing low-density cells. more than a lucky break--can lead to a "locked-in" situation as the small advantage Positive Feedback feeds on itself and ultimately eliminates the competition. The course of self-organization in complex The history of the VHS-Beta battle in the adaptive systems is often influenced by positive VCR industry is a prime example of this feedback. Rather than relying on negative phenomenon (Arthur, 1990). Despite the pos- feedback controls only (e.g., the thermostat that sible technical superiority of the Beta system, keeps temperature within a narrow range), the once the VHS system gained a slight edge in CAS uses the nonlinear interactions among its market share, the video outlets responded by parts to generate snowballing effects. The stocking more VHS-format tapes, which further dynamics of the positive feedback cycle are served to make VHS the recorder of choice self-reinforcing, and potentially amplify the among new consumers, and so on. Arthur impact of a small change or adjustment. Of suggests that a similar positive feedback loop course, the runaway effects do not always can determine the location of a country's appear to be constructive (such as a chain economic centers. If business enterprises benefit reaction of stock market crashes around the from being in close proximity to other firms, 50 EIDELSON then a self-reinforcing process will lead to paradigm in which a participant's positioning of industrial concentration in particular areas. a cursor in relation to a fixed point on a These areas need not even have any inherent computer screen represented his or her moment- merit over geographic regions that ultimately to-moment feelings about an acquaintance who fail to thrive. was perceived either positively, negatively, or ambivalently. While participants in the positive Intrinsic Dynamics and negative valence conditions gravitated over the 2-minute experimental session toward a The self-organization process does not inevi- position a fixed distance from the target point tably lead the CAS to a single fixed or static (the former-selecting a close location and the state. Indeed, many theorists and investigators latter a distant one), those in the mixed-valence have concluded that complex adaptive systems condition exhibited irregular oscillations in often exhibit internally generated fluctuations cursor positioning, suggesting that their evalua- beneath their macroscopic stability. For ex- tive judgments never stabilized on one fixed ample, Kelso et al. (1995) have reported that the point. dynamics of brain functioning in general and Finally, the analytical and simulation work of visual perception in particular are intrinsically Youssefmir and Huberman (1995) highlight the metastable. In one study using a computer- intrinsic dynamics of large multiagent systems screen depiction of the classic Necker cube, such as human society. The investigators participants were asked to press a mouse button designed models in which agents with incom- whenever their perception of the figure changed. plete information about the environment, or The investigators found "bursts of switching... bounded rationality (e.g., Arrow, 1991; Arthur, interspersed with prolonged periods during 1994; Sargent, 1993; Simon, 1957), competed which no perceptual Change takes place" (Kelso for limited resources. In efforts to optimize their et al., 1995, p. 75). individual outcomes, the adaptive agents were From the synergetics perspective, the multista- capable of switching strategies as the entire bility produced by such oscillations is the means system continued to evolve. Under these general by which the brain resolves ambiguity because it conditions, Youssefmir and Huberman found cannot recognize both interpretations of a that even when resource use reached a stable percept simultaneously (Haken, 1995). In this equilibrium state for the system as a whole, the regard, Kruse and Stadler (1993) conducted agents continued to switch strategies in pursuit several studies that revealed contextual and of greater individual returns. These persistent semantic influences on participants' perceptual intemal fluctuations intermittently produced stability when exposed to multistable patterns. bursts of momentary instability and volatility Similarly, Wildgen (1995) has documented before relaxing to equilibrium once again. numerous instances in which linguistic ambigu- ity (e.g., the phrase "some more convincing Bifurcations evidence") is tied to multistability in language perception. Stadler and Kruse (1995) have Although a complex adaptive system gener- concluded that multistability in perception is ates its own patterned evolution through intrin- actually quite common, and that higher cogni- sic dynamics and self-organizational tendencies, tive processes in the form of meaning contribute the CAS can also exhibit abrupt, nonlinear, and to the intermittent or permanent resolution of often dramatic transformations from one refer- these ambiguities. ence state to a qualitatively different one when In another area, Vallacher and his colleagues sufficiently perturbed by internal or extemal (e.g., Vallacher & Nowak, 1994; Vallacher, forces. From the dynamical systems perspec- Nowak, & Kaufman, 1994) have investigated tive, this discontinuity is called a bifurcation or the intrinsic dynamics of social judgment. Their phase transition (e.g., Prigogine & Stengers, findings contradict the commonly held assump- 1984) and has long been recognized in physical tion that evaluation of another person, once systems (e.g., Nicolis & Prigogine, 1989). formed, changes only in response to external Examples include a substance's change from influences such as new information or pressure liquid to solid (in response to the lowering of from others. The researchers used a mouse temperature), the thermal convection patterns of COMPLEX ADAPTIVE SYSTEMS 51

Benard cells (caused by an increase in tempera- deterministic aspects would become dominant" ture differential), and an earthquake or volcanic (p. 176). eruption (due to increasing subsurface stresses). This notion of discontinuous change and A more readily observable instance is the bifurcation has received both theoretical and sudden shift in a horse's gait as with increasing empirical attention from a variety of behavioral speed it switches from walking to trotting to and social scientists. For example, Merry (1995) galloping (Goerner, 1995). has suggested as a general proposition that the A critical variable measuring the forces that successive stages of human history alternate push the system toward bifurcation is often between periods of relative stability and predict- referred to as a control parameter (e.g., Haken ability on the one hand, and sharply contrasting 1983b; Nicolis & Prigogine, 1989; Nowak & intervals of instability and extreme sensitivity to Lewenstein, 1994). In general, a bifurcation small chance events on the other. Shermer occurs at a specific point along the continuum of (1995) has referred to this latter process as this parameter's values. Depending on the contingent necessity and provided an extensive particular system under consideration, the con- cataloging of fluctuations or triggers of change trol parameter could be, for example, the that may precipitate a society's abrupt reorgani- temperature differential between two locations, zation; they include inventions, discoveries, the concentration of a chemical in a solution, the famine, invasions, population explosions, and number of members in an organization, or the natural disasters. Similarly, Wiedlich and Haag degree of social pressure applied to an indi- (1983) have stated that even a few influential vidual. For parameter values below the bifurca- individuals can determine a society's direction tion point, the system will typically remain by triggering a revolution, but only if their relatively stable; that is, small changes in the actions come at an opportune time. control parameter will have little impact on the Within the realm of political science, Lust- ick's (1993) model of state-building and state- system's behavior. When the control parameter contraction provides a detailed example of approaches the bifurcation point, however, the discontinuous change in a CAS. Comparing the system becomes increasingly unstable and historical relationships between Britain and begins to display critical fluctuations (Haken, Ireland and between France and Algeria with the 1983a, 1983b). At the critical value itself, the current turmoil surrounding Israel and the West system reorganizes and assumes a significantly Bank-Gaza territories, he has proposed that the different form. political institutionalization of new territories-- There are many different types of bifurcations and the disengagement from them---consistently (Abraham, 1995; Nowak & Lewenstein, 1994). proceeds through three predictable stages: In what is perhaps the simplest case, the system struggles over incumbency, conflicts over re- has only one stable state available to it once gime integrity, and finally contention over beyond the bifurcation point. By comparison, ideological hegemony. Most noteworthy here with the pitchfork bifurcation the system selects are the two distinct thresholds that must be either of two divergent paths at the point of crossed to move from one stage to the next in bifurcation. Although incremental change in the either direction. Lustick refers to the threshold control parameter's values pushes the system points between stages as "discontinuities in the toward bifurcation, at the critical point the process of institutionalization" and adds that slightest random perturbation or intentional "moving from one stage to another entails a influence may determine which particular course shift in the order of magnitude of political is chosen. Both alternatives lead to renewed conflict that would surround efforts to change a stability, although a secondary bifurcation point particular institution" (p. 37). In short, these may subsequently be reached. Prigogine and thresholds represent bifurcation points which Stengers (1984) described this nonlinear process abruptly transport the political system to a as "a delicate interplay between chance and qualitatively different, reorganized state. necessity, between fluctuations and determinis- Bifurcations are also common phenomena in tic laws. We expect that near a bifurcation, the economic arena, where the gradual accumu- fluctuations or random elements would play an lation of destablizing stresses often leads to important role, while between bifurcations the discontinuities. Jacobs (1984) has provided two 52 EIDELSON examples: (a) the combined toll of rising costs emphasized that the educational interventions of and increasingly inadequate facilities inducing a counselors should induce sufficient tension to growing local business to relocate to another cause a bifurcation, while not creating so much city, and (b) rising demand for public transporta- instability as to preclude constructive change. tion coupled with only limited capacity for Along the same lines, Guastello, Dooley, and additional surface traffic leading to the construc- Goldstein (1995) have noted that facilitators tion of a new subway. Young (1991) has offered attempting to promote organizational change a somewhat different illustration, suggesting must foster an environment in which workers that a widening gap between an individual's unleash their "inherent propensity toward bifur- desire for goods and the financial resources to cation" (p. 269). This often involves encourag- acquire them may cause the abrupt adoption of a ing the recognition of discontent and amplifying criminal lifestyle. rather than dampening any areas of intraorgani- Some of Kelso's (1981, 1984, 1995) earliest zation disagreement. experimental work on bifurcations in human Bifurcation points have also been employed behavior involved phase transitions in hand in the study of close relationships. Baron, movements. Participants were first asked to Amazeen, and Beek (1994) adopted a dynamical move their index fingers rhythmically back and systems perspective in their analysis of Lev- forth in a parallel alignment with each other. inger's (1980) ABCDE model of long-term They were then instructed to progressively dyadic relations. In this five-stage model, Stage increase the speed of movement. When the A refers to attraction and is followed by Stage speed (i.e., the control parameter) reached a B, building a relationship. Of particular interest critical level, the index fingers involuntarily here is Stage C, which begins at a bifurcation switched from parallel to symmetrical pattern- point culminating in one of three forms of ing. relationship continuation: growing-satisfying, Tuller and Kelso (1990) documented a similar placid-static, or unstable-conflicO~ul. Both of phenomenon in human speech. When research the latter two forms lead to Stage D---deteriora- participants repetitively vocalized the syllable tion-and then Stage E, ending through separa- eep while progressively increasing their speak- tion. The growing-satisfying path, on the other ing rate (the control parameter), a phase hand, skips Stage D and instead continues until transition occurred and subjects spontaneously Stage E, ending through death. began reciting pee instead. Kelso (1995) also has reported more recent findings derived from Cusp Catastrophes the experimental analysis of magnetic fields and spatiotemporal patterning in the brain. He An important subgroup of bifurcations in concluded that "nonequilibrium phase transi- complex adaptive systems are those categorized tions offer a new mechanism for the collective as cusp catastrophes. The general framework of action of neurons, they provide the brain with a catastrophe theory translates discontinuous switching mechanism, essential for rapidly changes into mathematically complex topologi- entering and exiting various coherent states. cal forms (e.g., Thom, 1975; Zeeman, 1976, Thus phase transitions confer on the brain the 1977); the approach has proven controversial hallmark of flexibility" (p. 284). primarily due to imprecision in some of its From a more theoretical perspective, other applications and the overzealousness of some of researchers have identified directed discontinu- its proponents (Casti, 1994; Guastello, 1995). ous transformations as an important factor in Nevertheless, Casti (1994) has noted that psychological change. For example, many catastrophe theory does provide a useful tem- psychotherapists view bifurcation points as plate for understanding many processes. Simi- critical opportunities for positive change (Abra- larly, Latane and Nowak (1994) emphasized that ham, 1995). That is, a client experiencing "despite these criticisms, catastrophe theory increasing discomfort may be ideally situated to provides a convenient geometrical description discard worn-out, maladaptive behaviors and of how a continuous function may change into a adopt new, more promising ones instead. discontinuous one and allows us to predict a Similarly, in an analysis of academic compe- number of associated phenomena" (p. 229). tence in college settings, Torre (1995) has In a cusp catastrophe, the interaction between COMPLEX ADAPTIVE SYSTEMS 53 two control parameters determines whether the road" attitude on the issue. In two separate system experiences gradual or discontinuous studies of college students' attitudes toward change. Guastello (1995) has referred to these political propositions, and in a reanalysis of paired parameters as asymmetry and bifurcation attitude data collected from U.S. soldiers during controls. As long as the value of the bifurcation World War II, Latane and Nowak (1994) found variable remains low, macroscopic system strong support for the model's prediction that change occurs gradually in response to changes greater involvement with an issue is associated in the asymmetry parameter. If the bifurcation with the adoption of more extreme attitudes. control value is sufficiently high, however, the Another application of the cusp catastrophe to system abruptly destabilizes as the asymmetry a CAS is as a model of organizational change control crosses a threshold point, jumping from (e.g., Bigelow, 1982; Guastello, 1995). In one stable state to a qualitatively different stable Bigelow's conceptualization, organizational prac- state. tice-the sanctioned activities carded out by the Tesser and Achee (1994) have proposed that organization's members is influenced by two this cusp catastrophe model has broad explana- control parameters. The bifurcation control is tory value for understanding human behavior the degree of resistance to change, most whenever an individual's disposition to act in a frequently expressed as support for the organiza- certain way conflicts with social pressures tion's initial practice. The asymmetry control is against doing so. They presented romantic the amount of pressure for change. behavior as an example. When social pressures According to the model, when resistance to (the bifurcation control) against a young, change is low, increasing pressure to change will unmarried couple's involvement are minimal, produce a gradual transition or evolution in dating activities are likely to increase gradually organizational practice away from the initial as mutual attraction grows (the asymmetry conditions. On the other hand, if resistance to control). On the other hand, when social change is high, when growing pressure to pressures act as strong inhibitors, attraction may change reaches a critical threshold, a dramatic, grow with little behavioral manifestation until a revolutionary alteration in organizational prac- critical point is reached at which romantic tice results. Bigelow noted that despite the behavior abruptly leaps to high levels. model's limitations and qualitative nature, its Latane and Nowak (1994) have used a cusp predictions are consistent with actual accounts catastrophe model of attitude change (e.g., of organizational process and change. In particu- Zeeman, 1976, 1977) to generate the hypothesis lar, he emphasized that the model provides that attitudes tend to be distributed bimodally insight into how different developmental paths (i.e., as categories) when an issue is important to may result from attempts to influence the two a group, and tend to be normally distributed control parameters. "It may be possible to (i.e., as dimensions) when the issue itself is prevent change from occurring by keeping relatively unimportant. Within this framework, pressure for change low. Smooth change may be the importance of the issue to the individual can brought about by keeping resistance to change be viewed as the bifurcation control, and the low while increasing pressure for change. degree to which he or she receives negative Abrupt change may be brought about by versus positive information regarding the topic increasing resistance to change before pressure operates as the asymmetry control. for change becomes very great" (p. 38). For an uninvolving issue, the favorability of While many bifurcation models of complex the individual's attitude should be a smooth, adaptive systems thus far remain speculative continuous function of the valence of the and must await validation, Guastello (e.g., 1991, information about the topic. If the issue is an 1995) has employed catastrophe models exten- involving one, however, changes along the sively in his empirical studies of the workplace. asymmetry control (i.e., information valence) In an investigation of accident incidence among that cross a threshold point should produce a a sample of transit operators, Guastello (1991) dramatic, nonlinear shift in the individual's found that a cusp model was superior to a linear attitude. Furthermore, this region of instability model in fitting the data provided by the should prevent a highly involved person from participants' survey responses. Transit hazards, maintaining a noncommittal, "middle-of-the- such as violent passengers or riders who needed 54 EIDELSON to be reprimanded for rule infractions, operated ment, it may require a larger decline in attaction as the asymmetry control; the bifurcation before their dating behavior diminishes apprecia- control included social stressors like job insecu- bly. That is, for the same range of attraction, rity and role conflicts. Under conditions of high romantic activity will be higher during the stress, relative safety abruptly changed to dissolution of the relationship than it was during accident occurrence when transit hazards reach its creation. In regard to attitude formation a critical threshold. (Latane & Nowak, 1994), once an individual has In a related investigation with the same established a strong opinion regarding an issue sample of workers, Guastello (1992) determined of personal importance, he or she is likely to that cusp models were also more effective than cling to that position even when later confronted linear alternatives in explaining patterns of with considerable negatively valenced informa- specific stress-related illnesses (e.g., nervous- tion. In other words, the very same information ness, insomnia, high blood pressure, carpal on an issue may produce either a favorable or an tunnel syndrome). However, the relevant asym- unfavorable attitude, depending on how it metry and bifurcation variables differed, to compares in valence with previous information. some degree, from one illness to the next. In the Again, history matters. case of ulcers, for example, age, experience, and Similarly, organizational practice may display physical stress were the asymmetry controls hysteretic effects (Bigelow, 1982). If resistance while social stressors were the bifurcation to change is strong but pressure to change has controls. For high blood pressure, on the other been sufficient to produce a discontinuous hand, anxiety was more important than physical alteration in practice, that new mode of opera- stress as an asymmetry variable, and danger tion will likely persist even if significant replaced social stress as the primary bifurcation pressures to return to the old ways develop. variable. Finally, once workplace accidents or stress- related illnesses have been triggered, they may Hysteresis remain high despite successful efforts at moder- ating their precipitating influences (Guastello, An important identifying characteristic of all 1991, 1992). cusp catastrophes and many other forms of CAS bifurcation is hysteresis (e.g., Nicolis & Self-Organized Criticality and the Edge Prigogine, 1989). A hysteresis effect appears in a of Chaos dynamical system if the precise point of bifurcation along the control parameter (or The transition or bifurcation regions in which asymmetry variable) depends on the direction of the dynamic instabilities of a CAS are greatest change in that parameter. In this situation, the have received particular attention from some system's history influences its current state. That theorists and investigators. Bak and his col- is, for the same control parameter value, a leagues (Bak, 1994; Bak &Chen, 1991; Bak, system can be in either of two states depending Tang, & Wiesenfeld, 1988), for example, have on whether the control parameter was increasing proposed that the self-organization process itself or decreasing. Returning to the example of a is governed by a principle called self-organized horse's gait, with increasing speed a point is criticality. Self-organized criticality refers to the reached at which the animal abruptly shifts from tendency of a large dynamical system to a trot to a gallop. When the horse later slows naturally evolve to a critical state between order down, however, the speed at which it returns to a and disorder, often also called the edge of chaos trot may be slower than the shift point where the (e.g., Packard, 1988). The global features of earlier discontinuity occurred. Similarly, under such a system cannot be understood through an controlled conditions, the temperature at which analysis of individual parts; at the point of water turns to vapor can be above the tempera- self-criticality, either a large or small event can ture at which the vapor returns to liquid form. trigger a chain reaction of unpredictable magni- Each of the cusp catastrophes described tude (e.g., earthquakes, ecosystem extinctions, earlier manifests hysteresis to some degree. For or financial market collapses). example, once Tesser and Achee's (1994) couple The classic example of self-organized critical- have firmly established their romantic involve- ity is a pile of sand. As sand is slowly added COMPLEX ADAPTIVE SYSTEMS 55 from above, the pile's height increases until the tions underlying the emergence of all these slope reaches a critical state. At that point, any phenomena have much in common (e.g., a additional grains of sand will cause an ava- feeling of loss of personal control and responsi- lanche of unpredictable magnitude. In fact, the bility), and that each movement propagates distribution of sandslides is best described by a through a rapidly growing network of informa- power law, with a small slide far more likely tion exchange. Once the critical peak has been than a large one. But perhaps most intriguing is reached, however, even a small event (e.g., the the premise that the same conditions can demonstrated falsity of one claim) reverberates produce dramatically different outcomes on through the system causing the collapse of the different occasions. What remains relatively movement and a loss of interest by the general constant, however, is the critical state that the public. pile must return to before the next avalanche Other investigators have focused on the edge will occur. Bak (1994) also notes that once the of chaos notion, seeking theoretical or empirical pile is poised at the critical state, any analysis support for the view that complex adaptive based on individual grains of sand ceases to be systems evolve toward a critical state between useful. At that point, the pile of sand must be order and disorder. Langton (1990, 1992, 1995), viewed as a whole because even grains consider- for example, has proposed that this phase able distances apart are linked through an transition area is where a system has maximum elaborate network. adaptability and maximum effective information Scheinkman and Woodford (1994) have exchange. In the ordered regime, the system is applied the notion of self-organized criticality to too rigid and both information exchange among the observed instability of economic aggregates. components and responsiveness to a changing They propose that the significantly nonlinear environment are therefore limited. In the disor- and strongly localized nature of the interactions dered regime, on the other hand, the system is between different parts of the economy prevents too turbulent and its connections are too the law of large numbers from dampening disorganized to allow it to function at peak variations in demand or production. Because effectiveness. small changes in a particular unit's level of Langton further contends that a CAS will production can have large and nonuniform actually "slow down" when it reaches the phase effects on the economic activities of its immedi- transition state. Rather than moving quickly ate neighbors, inventory dynamics can propa- through this region, the system clings to the gate across time and between sectors in a large edge until pushed in one direction or the other. economy. Assuming such a pattern of linkages Indeed Kelly (1994) has proposed that in order and potential chain reactions, the authors to maintain itself in this poised state, the CAS concluded that final-goods demand (treated as will engage in a self-tuning process character- an exogenous shock) can cause a production ized by increasingly complex strategies and avalanche of any size, entirely unrelated to the feedback mechanisms. Similarly, Kelso (1995) size of the system. explained that complex adaptive systems often Bak and Chen (1991) also suggested a more hover near bifurcation points. He suggests that speculative example of self-organized critical- the brain itself "is poised on the brink of ity: "Throughout history, wars and peaceful instability where it can switch flexibly and interactions might have left the world in a quickly. By living near criticality, the brain is critical state in which conflicts and social unrest able to anticipate the future, not simply react to spread like avalanches" (p. 53). In a similar the present" (p. 26). vein, S hermer (1995) has offered a metaphorical Using computer simulations, Kauffman (1991, analogy in the rise and fall of various social 1993, 1995) has found that selection processes movements. Suggesting that "certain historical can drive simple Boolean networks (such as phenomena repeat themselves, not in specifics cellular automata) to this edge of chaos. He but in universals" (p. 77), he proposed that the suggests that the same phenomenon likely witch crazes of past centuries have equivalents operates with actual genetic regulatory systems. in modem day mass hysterias, moral panics, Along the same lines, Schuster (1994) reports alien abduction claims, and fears of Satanic that RNA viruses, faced with rapidly changing cults. Shermer has noted that the social condi- environments, do in fact appear to evolve near 56 EIDELSON the edge of disorder. For such viruses, stagna- of randomness in a system governed by tion enables the host organism to mount deterministic rules. effective defenses, whereas runaway mutation Crutchfield (1994) describes this phenom- can prove self-destructive to the virus. More enon in the following way: speculatively, Kauffman (1995) raises the possi- Where in the determinism did the randomness come bility that democratic forms of govemment from? The answer is that the effectivedynamic, which provide the best opportunity to resolve difficult maps from initial conditions to states at a later time, problems among conflicting interests because becomes so complicated that an observer can neither pluralism facilitates movement toward the phase measure the system accurately enough nor compute with sufficient power to predict the future behavior transition region where optimal compromise when given an initial condition. (p. 516) solutions can be found. Casti (1994) also points out that even when A Note on Chaos observing quite simple nonlinear behavior, it may still be impossible to know the system's In some complex adaptive systems, com- initial state precisely. And to further complicate pletely deterministic rules may nevertheless matters, investigators note that chaotic systems lead to unpredictable outcomes. This paradoxi- may exhibit nonchaotic behavior over much of cal phenomenon, initially identified in weather their domain (Gregersen & Sailer, 1993; Nicolis patterns and turbulent fluid flow, is caused by & Prigogine, 1989). sensitive dependence on initial conditions and is Inherent in the process underlying chaotic the particular focus of chaos theory (e.g., Baker behavior, however, lies the opportunity for & Gollub, 1990; Cambel, 1993; Crutchfield, surprisingly accurate short-term predictions. Farmer, Packard, & Shaw, 1986; Gleick, 1987; That is, there may be pockets of predictability Stewart, 1989). With chaotic behavior, exceed- even though long-term prediction is unattain- ingly small, perhaps even unmeasurable differ- able. Kelly (1994) summarizes the situation this ences in parameter values at one point in time way: "The character of chaos carries both good lead to large and ultimately unpredictable news and bad news. The bad news is that very differences in observed behavior at some later little, if anything, is predictable far into the point in the future. future. The good news is that in the short term, The classic summarization of this particular more may be more predictable than it first disproportionality between cause and effect is seems" (p. 424). Mandell and Selz (1994) also the so-called butterfly effect (Lorenz, 1993), note that even chaotic behavior may exhibit which suggests, for example, that the flap of a stability when viewed from the perspective of butterfly's wings in Brazil can cause a tornado in deep characteristics. For example, they describe Texas. Merry (1995) provides two additional the circumstances of a compulsive hand-washer. hypothetical instances. First, neighboring na- Although it may be impossible to anticipate tions developing under virtually identical eco- precisely when he or she will engage in this nomic and political conditions may subse- intermittent behavior, one can nevertheless be quently display dramatically different national confident that washing will occur with higher- cultures. Second, two brothers subjected to the than-normal frquency over any given period of same poverty-stricken childhood in an inner-city time. ghetto may grow up to be quite different from each other--one a renowned scientist and the How the CAS Responds other an incarcerated criminal. to Its Environment Sensitivity to initial conditions results from the inherently nonlinear nature of the equations Although the focus thus far has been on the underlying chaotic processes. Repeated itera- internal structure, dynamics, and self-organiza- tions, in which values from calculations at tional tendencies of CAS, these systems exist in preceding time points are "fed back" into the a larger environment that typically confronts system of equations to determine the values at them with a multitude of challenges, including the next time point, lead to a dramatic the actions of other coevolving complex adap- amplification in differences as the time horizon tive systems. The survival or success of the lengthens. The ultimate result is the appearance CAS, then, often depends on its capacity to COMPLEX ADAPTIVE SYSTEMS 57 effectively modify goal-oriented behavior in may fail to defeat an incumbent. Lacking full response to a changing environment. The information about the preferences of the entire adaptations are not necessarily passive; in many population, the challenger must rely on polls of cases the system responds actively with behav- randomly selected voters to refine its platform. iors designed to influence and perhaps even This iterative process may result in the party control the environment (Hubler & Pines, 1994). becoming stuck on a local peak, committed to a In this light, Huberman and Hogg (1986) platform that, although superior to all neighbor- observe that an important measure of adaptabil- ing platforms, nevertheless lacks the broad- ity is how well a system can function under based appeal necessary for victory. In short, the varying conditions with only minimal changes challenger's search method can lead it to think it in its structure. has identified a winning platform when, in fact, it has not. In a similar manner, it is common- Fitness Landscapes place for a person undertaking psychotherapy to report feeling stuck in a particular life situation; Several investigators have found the concept in some instances, this experience likely results of fitness landscapes useful in analyzing the from adaptations that have "trapped" the adaptation and coevolution of complex adaptive individual on a local fitness peak from which systems (e.g., Gell-Mann, 1994b; Kauffman, higher peaks are not directly accessible. 1993; Wright, 1986). In this metaphor, the agent This landscape perspective demonstrates how is pictured as moving about on an imaginary a complex adaptive system can sometimes topographical map. The landscape typically benefit from errors or random behaviors if such includes hills and valleys of varying degree, and actions inadvertently displace the agent from a the tallest peak represents the site of the agent's local peak, thereby increasing the likelihood that optimal fitness. Alternatively, the fitness land- the agent will reach the landscape's global scape can be viewed upside-down; from this maximum (Gell-Mann, 1994b). In fact, Kelly perspective, optimal fitness lies at the bottom of (1994, p. 470) views "honor your errors" as a the deepest basin. In either case, it is important guiding commandment for effective adaptation. to note that not all agents climb identical He advises that by nurturing small failures, a landscapes, and that the landscape itself can system can make large failures less probable. change. In short, complex adaptive systems That is, small cracks can prevent larger frac- differ from each other in the paths and obstacles tures. Indeed, errors are often renamed innova- to optimization. tions when they lead to a better problem solution Heylighen and Campbell (1995) have used a or a more adaptive path. Furthermore, tolerating fitness landscape approach in describing how minor mistakes instead of trying to correct or systems evolve through the twin processes of eliminate them also frees a system to focus on variation and selection. Although such evolution more important and more urgent functions. typically proceeds with small adaptive steps Of course, system errors or random behaviors gradually leading to higher ground, occasionally more often disrupt or prevent adaptive progress, the transitions temporarily take the system to especially when they are excessive in frequency somewhat lower regions. If these latter locations or magnitude. Many small steps toward a fitness are too low, the system risks elimination. But peak can be quickly undone by large, .misdi- without some nonadaptive excursions, the CAS rected movements (e.g., GeU-Mann, 1994b). is likely to get "stuck" on a local fitness Especially in a constant, unchanging environ- maximum and therefore never attain the more ment, such actions can prevent an agent from desirable global maximum. In other words, even maintaining fitness levels already achieved. evolution would cease because there would be External "noise" from the environment itself no direct path to increased fitness. can also contribute to a system's failure to Kollman, Miller, and Page (1992, 1995) successfully adapt. A noisy environment not document just such risks in their computer only complicates the system's task of sorting simulations of electoral landscapes in which usable information from random signals, but it political parties are adaptive agents competing can also disrupt efforts to focus attention and with each other for votes. In particular, they effectively respond to any particular input offer an explanation for why a challenging party (Hubler & Pines, 1994). Nor can the impact of a 58 EIDELSON sudden, catastrophic environmental event be uses a hierarchical set of roles--from the most overlooked. As Gould (1989) points out, such global to the very specific--to anticipate the accidents permanently alter the course of consequences of its own actions. If this look- history. Even the most fit can be undone by a ahead indicates negative consequences on the random bolt of lightning. horizon, the system can alter its current actions Whenever the environment or landscape is accordingly. However, this internal model is a populated by multiple adaptive entities, coevolu- truly effective predictive mechanism only if the tionary forces make the dynamics of adaptation system can analyze a situation and execute the increasingly complex. Indeed, the combined appropriate rules more quickly than the environ- activities of the individual agents create a larger ment changes--an especially challenging task CAS that incorporates all of them (e.g., in coevolutionary environments. Gell-Mann, 1994a). In order to reach their own Holland views the capacity to modify an respective fitness peaks, these coevolving agents intemal model as critical to the complex must simultaneously adapt to one another. As a adaptive system's effective functioning. Only in result, their optima are no longer fixed and a perpetually static environment can the same independent; the agents experience their shared rules always work, and even then fine tuning environment as a landscape that constantly may be advantageous. Furthermore, most CAS shifts and deforms (e.g., Kauffman, 1993, 1995; derive their rules from only a limited sampling Kauffman & Johnsen, 1992; Kollman, Miller, & of the environment. As with Gell-Mann's Page, 1995). schemata, Holland's rules undergo constant review by the system, competing with each Internal Models other in an evolutionary process designed to maximize the CAS's adaptability and chances of Many theorists and researchers have exam- survival. The complex adaptive system also ined the basic mechanisms that some complex forms plausible new rules from the component adaptive systems, such as human beings, make parts of tested rules. This process of recombina- use of in formulating actions intended to yield tion is a crucial element in the system's delicate positive consequences and greater fitness. Gell- balancing of exploitation and exploration. Ex- Mann (1994a, 1994b, 1995), for example, has ploitation here refers to the use of actions that explained that a complex adaptive system have produced beneficial outcomes in the past. actively searches for regularities in its own Exploration, on the other hand, refers to behavior and in the environment and then experimentation with new behaviors; these compresses incoming information into an orga- behaviors may prove to be extremely valuable nized collection of schemata. The use of or quite costly. Although there are attendant particular schemata in actual situations produces risks, without such exploration the CAS will consequences that, by means of feedback loops, eventually encounter a situation for which it has serve as input information for the modification no appropriate or effective response. of the schemata. This competitive cycle ulti- Kauffman (1994) has proposed a speculative mately leads to adaptation and learning. Gell- framework for how the intemal models of Mann has pointed out, however, that this process interacting individuals coevolve. Consistent is imperfect and that a maladaptive schema can with Holland's focus on look-ahead, Kanffman's persist uncorrected for a long time. For example, central premise is that adaptive agents strive to a person may perceive regularities where in fact maximize the accuracy of their predictions there is only randomness (e.g., superstition), or about each other. Through ongoing interactions, vice versa (e.g., denial). In this regard, Goertzel each agent develops a finite model of the other (1994) likens belief systems to immune systems, agent that will sooner or later prove inaccurate. suggesting that a set of faulty but mutually When a particular prediction fails, the individual supporting beliefs can act to "protect" an who was wrong alters his or her operative individual from the inputs of external reality. hypotheses about the other agent. This cognitive Holland (e.g., 1992, 1994, 1995) provides a change and the behavioral modifications coupled particularly detailed and rigorous analysis of the with it are likely, in turn, to create a failure in the processes that govern CAS responses to the second agent's internal model. When this environment. From his perspective, the system second agent then modifies his or her own COMPLEX ADAPTIVE SYSTEMS 59 preferred hypotheses and behavior, the first however, potential victims would become less agent will shortly thereafter discover a new vigilant, which would lead to a rekindling of failure in his or her own most recent internal opportunities for would-be thieves. In short, as model. And so the cycle continues. each group alternately becomes too successful Kauffman hypothesizes that this coevolution- in relation to the other, the seeds are planted for ary process produces dynamical changes in the its own at least temporary demise. complexity of each agent's internal model. Baron, Amazeen, and Beek (1994) have Following a disconfirmation, an agent will proposed that a similar coupling may describe generally adopt a simpler, more general model majority-minority relations. If the majority that is less likely to be wrong, but also is less grows too large (and the minority too small), it useful for precise predictions. As the agent may cease to adequately monitor the quality of gradually accumulates reliable data from new its functioning (e.g., values and goals) and interactions, he or she will find it advantageous therefore suffer the loss of disenchanted support- to once again develop a more detailed internal ers. If the resulting increase in the size of the model of the second agent's behavior. This minority is too dramatic, however, the overall process of adding complexity continues until the group cohesiveness can be shattered--a trou- first agent is once again confronted with a bling consequence for even the minority support- disconfirmation. In short, Kauffman suggests ers themselves. Indeed, a further shift of that a coevolutionary agent's internal model is allegiances or splintering of the group may driven back toward a self-organized critical occur before the minority is able to achieve state, poised at the edge of chaos, whenever it majority status. Because healthy group function- strays too far away. ing may therefore depend on a certain ratio of majority-to-minority sizes, the authors de- Coevolutionary Relationships scribed the challenge as follows: At issue here is getting outgroup strength to be high Coevolution among CAS takes many differ- enough to increase ingroup cohesiveness given that if ent forms; among the most common is the outgroup pressure is too weak, internal cohesiveness predator-prey relationship. In nature, these may suffer. On the other hand, if outgroups grow too pairings of species often display either a steady powerful, internal cohesion, instead of increasing, may jump in the opposite direction, with members leaving equilibrium or an oscillating Lotka-Volterra the group. (p. 136) cycle such as that observed between the Canadian lynx and the snowshoe hare (Sig- In contrast to the cycling described above, mund, 1993). In this latter case, an initial competition among species or complex adaptive increase in the number of predators leads to a systems can sometimes lead to a coevolutionary decline in the availability of prey; this constraint "arms race." This phenomenon is epitomized on food supply then reduces the number of by van Valen's (1973) Red Queen hypothesis, predators that can survive, thereby enabling the which refers to any situation in which continu- prey population to grow once again. The ing adaptation is necessary just to maintain increased availability of prey, however, will relative fitness. Heylighen and Campbell (1995) precipitate a rise in the predator population, and emphasize that such an arms race is most likely SO on. between similar systems that depend on the Nowak and Lewenstein (1994) have sug- same resources; the outcome can be detrimental gested that this same cyclical pattern may fit the to all parties involved. They offer as an example system dynamics of pickpockets and naive the forest trees that grow ever taller--and victims (i.e., those who fail to adequately protect increasingly vulnerable--as they compete with themselves from theft) in contemporary society. each other for sunlight. Such a model would work in the following way: Similar coevolutionary arms races can also be With many pickpockets at work, the number of seen in human society. Saperstein (1990), for people willing to walk the streets unprotected example, has described the commonplace esca- would quickly diminish. This decline would lation of weapons development and deployment then curb the profitability of picking pockets, between hostile nations. Each nation's security forcing many to find alternative means of policy decisions are based on an evaluation of financial support. As the pickpockets vanish, the armament stocks of their opponents. The 60 EIDELSON rapid response capabilities provided by strategic discovered even more complex creatures such as nuclear weapons only serve to tighten these social hyper-parasites that could self-replicate interconnections. Saperstein concluded that "One only when together in groups, and cheaters that cannot be confident of 'pushing' an opponent would infiltrate these social groups and steal the safely around the 'policy field' when there may exchanges between them. It is of interest here be a precipice in that field over which each that Hillis (1992), in his own work with sorting might drag the other" (p. 179). Mayer-Kress networks, discovered that optimization proce- (1990), in analyzing his own simulation models, dures were actually more effective and more added that the arms race between nations can be efficient when coevolving parasitic codes were precipitated by even a small change in one included in the programming environment. By nation's response to a perceived threat from uncovering and exploiting any weaknesses, the another. parasites pushed the system away from local Fish (1994) speculated that the arms race maxima and toward the optimal global solution phenomenon is also central to the coevolution- instead. ary battle between government forces and the Similarly, Holland (1994, 1995) has devel- purveyors of illegal drugs: oped his ECHO computer model to simulate the When the police get more firepower, the drug lords flow of resources among reproducing artificial escalate their armaments. Greater ingenuity in tracking agents. The world in which these agents move is illegal funds is met by improved methods of hiding a connected array of sites, each of which them. Stiffersentences for adult drug dealers lead to the provides variable amounts of renewable re- recruitment of children who are not subject to those penalties. (p. 15) sources. An agent must obtain a sufficient reservoir of such resources in order for it to Fish has also maintained that the symmetrical successfully self-replicate. In addition, the escalation has led to both greater violence and agents also directly interact and exchange greater drug abuse. It is interesting to note Fish's resources with each other. They vary, however, expectation that any change in drug policy will in their abilities to force the outcome of an likely be discontinuous--the kind of sudden interaction, resist another agent's own efforts, alteration that typifies a bifurcation point. and organize themselves into larger, more The computer simulations of investigators complex meta-agents. The ECHO system speci- outside the social science arena also provide fications can be designed to study phenomena pertinent insights into the coevolutionary dynam- such as interactions in natural ecosystems, the ics of interacting CAS. Ray (1992, 1994), for evolution of organizations, economic activity in example, created an entire virtual computer modern societies, and immune system re- world called Tierra and initially populated it sponses. with self-replicating machine-code creatures Finally, Hubler and Pines (1994) have con- that competed for limited CPU time and ducted numerical experiments investigating the memory space. Tierra also included a reaper interaction patterns of CAS dyads. In their function to cull flawed algorithms from the simulations, each agent's primary goal is to "soup" as well as a mutation function to mimic discover regularities in their shared environ- biological evolution. Over time, metabolic ment; meanwhile, even without direct communi- parasites capable of using the procedure codes cation, the paired agents can both enhance and from other creatures appeared and multiplied. diminish each other's predictive abilities. De- This led to a decline in the original host pending primarily on the combinations of active population, and then a significant drop in the versus passive adaptation employed by the number of these parasites. After a subsequent agents, the researchers uncovered a variety of rebound in the size of the host population, coevolutionary dynamics. For example, a leader- parasites proliferated once again. follower configuration at the edge of chaos At the same time this cycle was unfolding in tended to be the most stable paired arrangement. Ray's study, an evolutionary arms race escalated Hubler and Pines also found that active in which host creatures developed immunity to adaptation was preferable to passive adaptation the parasitic invaders, then the parasites found under most circumstances, and that the agent ways to circumvent the immunity, and so on. with the more complicated strategy was gener- After the succession of many generations, Ray ally victorious in any direct competition. COMPLEX ADAPTIVE SYSTEMS 61

Game Theory ism, and evolutionary stable strategies" (p. 295). Lindgren also discovered that agents were able Analyses of coevolutionary behavior in com- to limit how successfully competitors could tune plex adaptive systems often rely directly or their strategies by including occasional mistakes indirectly on game theory principles, which can or random choices as components of their own generally be applied to any potential conflict strategies. situation where the outcome is determined by Similarly, Marks (1992) has analyzed politi- the participants' choices. Formulated initially by cal change in authoritarian systems from a game von Neumann and Morgenstern (1944) as a theory perspective; his particular focus is on the model for economic behavior, game theory has strategic interactions that characterize mass proven useful in many other contexts, including protest by the political opposition against the the study of cooperation (e.g., Axelrod, 1984), ruling elite. Each of these coevolving groups can escalation (e.g., Shubik, 1971), and evolution adopt either of two policies: the ruling elite can (e.g., Maynard-Smith, 1982). The most well choose to tolerate or suppress its opponents and known of these games is the Prisoner's Di- the political opposition can choose to operate lemma, although others such as Chicken, Stag within the system or challenge it. However, the Hunt, and Deadlock can also be viewed as situation is further complicated by factions building blocks of complicated coevolutionary within the ruling elite and, because mass protest interactions (Kelly, 1994; Poundstone, 1992). requires coordination among a large number of An important distinction made by game individuals, by the decisions of each opposition theorists is whether the situation under consider- member. As a punitive measure against a ation is a zero-sum or non-zero-sum game. The suppressing ruling elite, a public protest will former describes a strictly competitive situation have the desired impact only if it is of sufficient in which the combined total payoffs for the size; otherwise, those who protest may be worse players are fixed. That is, one agent can benefit off than the nonprotesters. only at the expense of another agent. In contrast, The system dynamics, then, share some a non-zero-sum game can provide positive or features with other collective action problems. negative outcomes to all players depending on Here, the eventual number of protesters depends their collective actions (e.g., Luce & Raiffa, on the potential participants' own expectations 1957). In the classic Prisoner's Dilemma, for about whether or not a critical mass will be example, each agent's best individual outcome achieved. Furthermore, the elite regime's ac- is obtained by defecting, but their best combined tions (e.g., mobilizing additional troops) contrib- outcome requires mutual cooperation. Interest- ute to determining how many of the political ingly, it is not unusual for agents to misperceive opposition are necessary to constitute a critical their payoff matrix; they often behave competi- mass. For all involved, information about tively when cooperation would be more profit- intentions is crucial. For example, if the ruling able for all (Axelrod, 1984). elite should decide to adopt an attitude of Of particular relevance to coevolving CAS toleration rather than suppression, the implica- are situations that involve repeated interactions tions can be profound. As Marks (1992) over time--that is, iterated games. When agents explains: "The critical task for the political recognize that they may have multiple encoun- opposition in this scenario is to limit protest ters (perhaps even indefinitely) with each other, despite the penchant of individual oppositionists their strategies often become more complicated to protest previously bottled-up anger, griev- as memory of past outcomes and anticipation of ances, and demands" (p. 411). That is, the future contact affect current decisions (e.g., leadership must now reverse course and encour- Axelrod, 1984; Poundstone, 1992; Sigmund, age a policy of working within the system for 1993). For example, Lindgren (1992) designed continued change. Indeed, mass protest at this an elaborate computer simulation of an iterated juncture could be self-destructive if it induces Prisoner's Dilemma game in order to study the ruling elite to reinstitute a policy of coevolution in an artificial population. He suppression. observed a variety of evolutionary phenomena, As a final illustration, Messick and Liebrand including "periods of stasis, punctuated equilib- (1995) have employed the Prisoner's Dilemma ria, large extinctions, coevolutions of mutual- to examine changes in the frequency of coop- 62 EIDELSON eration over time. Using computer simulations, the merits and shortcomings of the CAS they created artificial populations in which all of perspective will ultimately require an interdisci- the agents relied on the same strategy in plinary dialogue. In this final section, several of deciding whether to cooperate or defect. Three the central issues are highlighted. different decision heuristics were explored: By way of a brief review, the key tenets of the tit-for-tat, in which the agent adopts the choice CAS perspective are summarized well by each made by the neighbor with which it most word in the term complex adaptive system. recently interacted; win-stay~lose-change, in Complex conveys many attributes, the clearest which the agent compares its most recent of which may be the nonlinear nature of the outcome with those of its neighbors and then world around us. According to complexity maintains its choice if the comparison is theory, small events (such as someone's slightly favorable or switches if the comparison is different idea) can have dramatic effects, and unfavorable; and win-cooperate/lose-defect, in seemingly large events (such as a long-awaited which the agent cooperates if its previous conference of world leaders) can have no outcome was favorable in comparison to its discernible impact at all. Simple processes (like neighbors and defects if social comparison a disagreement among family members) can revealed the previous payoff to be unfavorable. mushroom out of control; intricate or massive Under all these conditions, the agent's decision structures (for example, the former Soviet heuristic was applied successively to whichever empire) can collapse virtually overnight. Abrupt of its neighbors (from among the eight surround- change (such as a calm neighborhood trans- ing cells of a larger grid) was randomly selected formed into a riot-tom community) is often the for its next interaction. norm rather than the exception. In summarizing their many findings, Messick Adaptive reflects the perspective's focus on and Liebrand (1995) emphasized that significant the change and evolution that characterize levels of cooperation persisted over time-- individuals, groups, and societies. Equilibrium regardless of which choice strategy was homoge- states (for example, group consensus on an neously applied---as long as the overall popula- issue) are viewed as transient because they are tion size exceeded a threshold value. In addition repeatedly disrupted by both internal phenom- to the importance of group size, they found that ena (such as one member's increasing animosity the particular methods used in evaluating toward another) and external influences (such as outcomes also made qualitative differences in new information about a competing group's the dynamics of cooperation. In describing the latest strategy). Periods of disorder and instabil- cooperation as an emergent social phenomenon ity (for example, the turmoil of adolescence) are that cannot be adequately explained on the basis recognized as natural and necessary stages on of individual actions, Messick and Liebrand the path toward greater self-organization. The concluded that "simple behavioral rules, rules search for optimal fitness, however, often instantiating the most rudimentary forms of includes frequent detours and shifting terrain as adaptive social interaction, can lead to unex- other individuals or groups struggle to adapt on pected global patterns in large groups" (p. 144). the same landscape. The final word system emphasizes intercon- Implications for Behavioral and Social nections. A CAS can be readily apparent (as in Science Research the case of a close-knit family), or shrouded and concealed (as with the relationships among This overview of complex adaptive systems distant nations). As a result of the dynamical has covered considerable ground. Many con- interactions among the component parts of the cepts have been presented, and numerous system, collective behavior emerges (such as examples have been provided in an effort to political revolt) and often catches people by give the reader a broad-based view of CAS surprise--no matter how well we understand the applications in the behavioral and social sci- individual elements separately. Therefore, policy ences. In the process of answering some measures (for example, economic tariffs, manda- questions, other concems have undoubtedly tory drug testing, or parental limits on sibling been raised. As noted in the introduction, given disputes) frequently have unintended conse- current knowledge, a conclusive evaluation of quences as they work their way through a COMPLEX ADAPTIVE SYSTEMS 63 network of intermediaries, each of which objective understanding of the world in which contributes its own fingerprint to the message it we live, behavioral and social scientists are transmits. Simple cause-and-effect relationships burdened with the additional expectations of evaporate, leaving instead patterns and regulari- both explaining and improving the world(s) we ties to decipher. create. Loye and Eisler (1987) refer to this as the The behavioral or social scientist faces many "normative aspect of social theory, or the challenges in translating complexity theory requirement of attention to the systems guidance principles, originally formulated in the natural question of ideal developmental forms that must sciences, to areas such as psychology, sociology, be the prime concern of all policy makers" (p. economics, or political science. Most clearly, 56). In the context of complex adaptive systems, people have characteristics that make them this mission includes such goals as enhancing different from purely chemical or physical communication patterns, redressing the inequi- systems. For example, although the evolution of table distribution of benefits within a society, human social systems may at times be mis- uncovering peaceful solutions to group or guided, it is rarely blind. Our self-organizing international conflicts, and discovering mecha- enterprises are distinctive because they typically nisms to make organizations and governments involve attempts to intelligently plan structures more responsive and effective. (e.g., Weidlich & Haag, 1983). This aspect alone In short, the added complexity of CAS in the contrasts sharply with the unknowing move- behavioral and social sciences can create serious ments of fluids or gases. Furthermore, even if and sometimes intractable modelling problems. individuals are generally limited in their ration- Indeed, many adherents to the complexity ality and not always intentional in their actions, paradigm acknowledge that, once outside the it remains problematic to adequately control or natural scientist's laboratory, researchers may be eliminate the influence of their awareness and limited to qualitative analysis. Weidlich and perceptions. Hinterberger (1994) summarizes Haag (1983), for example, suggest that math- the situation in the following way: "All physical ematically accurate and detailed descriptions of and biological laws and processes apply to microlevel processes may be unattainable, social processes but special aspects of human though they believe significant insights can be abilities, human culture and social life require a garnered nonetheless. In this regard, Nowak and broader theory that also allows us to explain the Lewenstein (1994) see considerable value in specialties based on the specifically human simply uncovering similarities between specific ability of active, conscious and intelligent aspects of dynamical systems and human social decision-making" (p. 38). behavior. But at the same time, it is necessary to More generally, the individual components distinguish thorough qualitative analyses--such making up systems in the behavioral and social as many of the investigations reported here-- sciences (e.g., people, groups, societies) tend to from those in which complex systems terminol- be far more complicated than the corresponding ogy is used in a merely metaphorical manner. components that create systems in the natural It is important not to overlook the intellectual sciences (e.g., molecules). Indeed, a single hazards associated with developing elegant living organism is a collection of many simpler metaphors while forsaking the construction of CAS. Additionally, in contrast to physical or accurate models. A blurring of the two ente- chemical systems, the interactions among the prises can inadvertently occur when the CAS same group of individuals often take a multitude models of behavioral and social scientists suffer of different forms (Weidlich & Haag, 1983). As from oversimplification. For example, Barton a result of this greater complexity, it can appear (1994) has pointed out that if consequential as if deterministic causal laws do not govern features of a system are ignored in order to make social phenomena. Accurate measurement in the investigator's inquiry and analysis more itself can be a significant obstacle for the social manageable, the resulting model may hold little scientist attempting to develop an explanatory promise for improving understanding. This model of a complex adaptive system (Nowak, "discontinuity between model and reality" Vallacher, & Lewenstein, 1994). (Barton, 1994, p. 10) can be further exacerbated In a related vein, whereas natural scientists by the difficulties or impossibility of testing direct their efforts toward heightening our precise hypotheses, which requires that the 64 EIDELSON system under investigation be sufficiently iso- influence can profoundly impact the system; in lated from the external factors impinging on it the latter circumstance, the system eventually (Barton, 1994). Echoing this last point, Kelso returns to its equilibrium state regardless of the (1995) expresses concern about the paucity of outside force's magnitude. actual experimental studies of complex adaptive For the behavioral or social scientist, the systems: "Little contact with experiment is identification and investigation of CAS can be made, and interplay between theory and experi- facilitated in several ways. Nowak, Vallacher, ment, so crucial to the development of science, and Lewenstein (1994) have recommended is lacking. Behavior as a source of insight into looking for regularities or patterns rather than principles of self-organization ... is virtually focusing solely on uncovering one-way causal ignored" (p. 28). links between variables; bidirectional causality, But despite obstacles to behavioral and social in which each variable is simultaneously both a science applications, significant insights rel- cause and an effect, is commonplace in complex evant to research design are provided by the systems. Within these observed patterns of complexity paradigm. For example, a dynamical behavior, it may be possible to detect signs of systems orientation reveals that qualitatively nonlinearity, including bifurcations and hyster- different behaviors do not require different esis. Such identifications obviously require explanatory mechanisms (Kelso, 1995). In this multiple observations over time (e.g., time- way, periods of linear change and episodes of series analyses). More generally, the mecha- nonlinear discontinuity in a system's evolution nisms underlying a system's organization can be can both result from the same set of parameters. clarified both by observing as the system's Similarly, the CAS perspective encourages intrinsic dynamics unfold naturally and also by investigators to consider the possibility that deliberately perturbing the system and evaluat- change in a system may be a reflection of its ing its response (Nowak, Vallacher, & Lewen- internal dynamics alone. Although a sudden stein, 1994). qualitative transformation in an object of study In a related manner, Kelso (1995) has stressed often leads the researcher to suspect that a new the importance of focusing on a system's variable has entered the picture, complex instabilities. It is at these critical points that systems can exhibit such changes in the absence changes in patterns of behavior are most readily of new or external influences (e.g., Newtson, distinguished. Furthemore, such points can offer 1994; Nowak, Vallacher, & Lewenstein, 1994). the best opportunity to identify the control Paradoxically, then, the CAS approach may parameters that are in all likelihood relevant to actually provide simpler explanations for a the system's linear behavior as well. More variety of phenomena. generally, Kelso advises that knowledge is The complexity perspective also illuminates necessary in three areas in order to understand a the interplay between the fragility and stability particular complex adaptive system: (a) the that characterizes many of the phenomena parameters that act on the system, (b) the explored by behavioral and social scientists. On individual components that compose the system the one hand, under certain conditions even a itself, and (c) the behavioral patterns that small change in a system's parameters can emerge from the interactions among these produce dramatic effects. According to Holland components. (1995), locating these lever points is essential The effective study of complex adaptive for producing major predictable and directed systems also requires the use of appropriate change in the system. On the other hand, within techniques for data analysis. Important nonlin- different parameter ranges, the same system ear relationships among variables--a hallmark stubbornly refuses to change, and displays a of CAS----can go undetected if only traditional constancy that confounds all efforts directed statistical methods are used (e.g., Barton, 1994). toward its alteration (whether measured in time, As Holland (1995) explained, "Nonlinearities money, or creative energy). In regard to this mean that our most useful tools for generalizing discrepancy, Nowak, Vallacher, and Lewenstein observations into theory--trend analysis, deter- (1994) explained that a system's resting state mination of equilibria, sample means, and so equilibrium can range from unstable to super- on--are badly blunted" (p. 5). For example, stable. In the former condition, a slight external critical information can be lost when parameter COMPLEX ADAPTIVE SYSTEMS 65 values are averaged; such an approach often ment is all but impossible in this situation. We disguises or conceals temporal phenomena (e.g., cannot follow the traditional experimental path, cycles) characteristic of complex adaptive sys- varying seleqted variables under repeated runs tems (Nowak, Vallacher, & Lewenstein, 1994). while holding\~most variables fixed, because Similarly, the traditional cross-sectional study controlled restarts are not possible with most is of limited usefulness in analyzing behavioral cas, and because some cas operate over long or social systems that evolve over time (e.g., time spans" (p. 160). In a similar manner, many Gregersen & Sailer, 1993). Although inherently other investigators have emphasized that the more difficult and expensive, longitudinal stud- theoretical models applicable to complex adap- ies with multiple observation points enable the tive systems are often so complicated that researcher to more realistically capture such a computer simulations become necessary be- system's dynamics. Even with this approach, cause even advanced analytical mathematics abrupt phase transitions may nevertheless be prove insufficient (e.g., Axelrod, 1986; Koll- difficult to detect reliably because they typically man, Miller, & Page, 1995; Messick & Li- occur within only a narrow band of the system's ebrand, 1995; Miller, 1995; Nowak, Vallacher, full range of operation (Kruse & Stadler, 1993). & Lewenstein, 1994). In a related manner, Gregersen and Sailer (1993) Another important virtue of computer simula- have pointed out that the examination of chaotic tions is that this methodology forces the systems can be perplexing because they can investigator to carefully and precisely specify a display ordered behavior over a large part of model as a preliminary step in the research their domain. process. The exercise of writing the program As suggested by the many examples pre- itself can provide a test of the theory's sented in this paper, the computer simulation or completeness while highlighting any internal numerical experiment is an especially important contradictions (Nowak, Szamrej, & Latane, tool for behavioral and social scientists conduct- 1990). When the simulation is then run, the ing complexity research. Indeed, simulations of consequences of the specific rules and relation- actual phenomena are far more common than ships among variables can readily be observed. traditional experiments in this arena. A large and Mayer-Kress (1990), for example, pointed out diverse group of investigators have endorsed that the use of simple computer models can and used the methodology (e.g., Allen, 1982; uncover "possible counterintuitive consequences Axelrod, 1986; Glance & Huberman, 1994; of decisions that appear to be good solutions at Holland & Miller, 1991; Kauffman, 1993; the time they are made" (p. 181). Mayer-Kress, 1990; Messick & Liebrand, Several other benefits to the simulation 1995; Nowak, Vallacher, & Lewenstein, 1994), approach are detailed by Holland and Miller although the simulation approach has its draw- (1991). First, the use of artificial adaptive backs too. For example, it inevitably puts some agents compels researchers to clearly specify distance between the researcher and his or her their assumptions and also enables them to subject of inquiry (e.g., Kelso, 1995). Further- observe the behavior of their "subjects" step-by- more, the models on which the simulations are step as it unfolds. Second, important parameters based may themselves be faulty or oversimpli- such as the amount of information available to fied (e.g., Barton, 1994). Important variables the agents, their expectations, and how quickly may inadvertently be excluded; the relationships they learn can be precisely determined and among parameters may be misspecified. Be- systematically modified. Third, the features of cause of these and other potential distortions, the environment can also be varied to explore comparing simulation results to real-world alternative scenarios. Finally, and of no small behaviors and social patterns is a mandatory significance, the artificial agents' "infinite pa- step in the model-building and testing process. tience and low motivational needs ... implies It is important to recognize that the inherent that large-scale experiments can be conducted at complexities of the phenomena of interest place a relatively low cost" (p. 366). limits on the methods by which researchers can The complex adaptive systems perspective, effectively study them. Writing about this issue, with its dynamical models and computer- Holland (1995) stated, "The traditional direct intensive research strategies, should not be bridge between theory and controlled experi- viewed as a panacea for the puzzling and 66 EIDELSON intricate issues with which behavioral and social Axelrod, R. (1986). An evolutionary approach to scientists must grapple. Nevertheless, this paper norms. 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