A A GENERAL ARTICLE - R L T I F Artificial Life and Philosophy E
ABSTRACT
Alvaro Moreno Artificial Life is developing into a new type of discipline, based on computational construction as its main tool for exploring and producing a science of life “as it could be.” In this area of research, the generation of rtificial Life (A-Life) has been defined as the A-LIFE AS A complex virtual systems, in A place of the traditional empirical study of all possible life through its artificial production. This COMPUTATIONAL definition raises three important issues: First is the very sense RESEARCH PROJECT domain, has become the actual of the term “study,” for A-Life is not only an epistemic or a object of theory. This entails a Although A-Life is not necessarily to profound change in the tradi- purely theoretical process but also a technical activity, because be understood as a computational tional relationship between in A-Life the objects of study are literally created through tech- ontological, epistemological and science, its major research activity nological action. Second, the actual meaning of “lifelike sys- methodological levels of analy- takes place in the computational do- tems” (or systems that show “lifelike” behavior) becomes sis, which forces us to recon- main. As mentioned above, the sider the differences apparently much more complex (and controversial) than in traditional most prevalent meaning of the term firmly established between biology, since this concept has become understood in a much artificial in A-Life research specifi- science and philosophy. Even if wider sense than that of empirically real biological systems. the frontiers between these two cally refers to the generation of vir- Thus, as C. Emmeche has pointed out, A-Life is founded as a kinds of knowledge do not tual systems in the computational modal discipline, establishing as its own objective the study of completely disappear, new, universe. As a matter of fact, this fea- dynamic, complex, technologi- life “as it could be” and not simply “as we know it” (even if we ture is not original to A-Life. For the cally mediated interactions are include here any extraterrestrial forms of life that might be being developed between them. past 50 years there has been a strong discovered in the future) [1]. Last, but not least, the idea of tradition in the general study of dif- “artificiality” should also be subject to examination. In addi- ferent types of systems that makes a tion to its generic sense of human construction, the term ar- radical distinction between the informational-organizational tificial has a double-sided peculiarity in the context of A-Life. aspects of a system and its energetic-material ones. This dis- On the one hand, it has a paradoxical meaning, resulting tinction already existed at the core of such disciplines as cy- from the idea that such humanly constructed systems should bernetics, computer and systems sciences and AI. These be capable—like natural living beings—of exhibiting cre- disciplines share with A-Life a common approach based on the ativity. So-called emergent behavior, capabilities, morphology, idea that the material or energetic aspects of an organization etc., sought by A-Life designers must be understood precisely do not affect its logical essence. Hence, even the admitted ne- as a form of indirect human creation [2], what Langton has cessity of including a good deal of ancillary machinery for the described as “getting the humans out of the loop,” designing actual implementation of any material system [4] would not artifacts able to perform nontrivial, unpredictable activities, be significant for modeling the “actual organization” of that so that the machine itself could appear as if it were endowed system. That is why researchers’ interest and activity is mainly with creativity. That is to say, one of the essential features of focused on the study of virtual systems generated in a compu- A-Life is that the artificially created system should display tational environment. Even most research in the domain of some type of agency, which allows us to speak (without falling physical realizations, such as the design of autonomous robots, into contradiction, although somewhat paradoxically) of au- is largely influenced by the aforementioned philosophy, since tonomy in such cases. And on the other hand, artificial has the construction of the physical “body” of the robot is still con- the peculiar meaning (not exclusive but prevailing), as in ar- sidered independently of its behavior. tificial intelligence (AI), of virtual “construction” as opposed to physical realization [3]. The complex combination of all these elements has pro- vided A-Life with an identity as a separate discipline, distinct not only from traditional biology but also from the whole set of traditional empirical sciences. The idea that a living entity subject to study is to be generated by a human agent—and, furthermore, in a computational universe—is truly suggestive; nevertheless, it also brings up many novel issues and chal- lenges.
Alvaro Moreno (educator), Department of Logic and Philosophy of Science, University of the Basque Country, Post Box 1249, 20080 San Sebastián, Donostia, Spain. E-mail:
© MIT Press LEONARDO, Vol. 35, No. 4, pp. 401–405, 2002 401
Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/002409402760181204 by guest on 25 September 2021 A A - R L T The roots of the computational ver- whether these models might allow com- that the computational world does not I sions of both AI and A-Life lie in the idea putational simulations or not, the mod- constitute a proper matter for study; it F E of functionalism. This position assumes els involve the pre-existence of a should rather be considered a complex and asserts that the specific materiality reference system, whose behavior is to be social practice that involves the design, that sustains a certain capability (mental, totally or partially reproduced. construction, maintenance and use of in- biological or otherwise) is not relevant The case of A-Life, however, is radically tentional artifacts [10]. Whatever answer [5]. Accordingly, functionalists claim that different. A-Life researchers attempt to may be given to these questions, it will biological phenomenology is the exclu- create not only a symbolic model of a liv- certainly have methodological implica- sive result of an organizational arrange- ing system, but also a symbolic living ob- tions, since all these problems are closely ment, rather than of a particular material ject. Accordingly, these computational related to that of establishing the criteria implementation of it. In fact, the ques- “models” are elaborated without direct for evaluating the hypotheses that the tion of whether those organizational and precise reference to empirical bio- very design of such systems attempts to arrangements are sustained by carbon or logical reality. C. Emmeche regards them test. silicon molecules or by patterns of elec- as “second-order simulacra, that is, copies trons in a computer is considered com- of the copies themselves” [7], generated pletely irrelevant. This is the reason why not as abstractions of empirical biologi- THE PROBLEM OF Langton [6] has defended the idea of cal systems (as in the case of concepts and “EMPIRICAL” EVALUATION universalizing classical biology by ab- theories of biology, which would be “first- I shall, for simplicity, use the term stracting the materiality of biological order simulacra”) but of the theories “model” hereafter to designate those vir- phenomena when studying such phe- themselves. Their main goal is to allow a tual systems created in computational nomena: he assumes this study can take new means of “computational experi- media with the aim of enlarging our place in a purely formal organizational mentation” to enable us to “discover” the knowledge about the universal laws of domain. Accordingly, the huge potential universal principles of living systems. life. Taking this into account, the funda- for exploration of virtual organizations Thus, proponents of “strong” A-Life mental problem in the methodology of in the computational realm becomes for explicitly claim that computational sim- A-Life research programs is that their A-Life researchers a way of “experiment- ulations of living systems may really come means of evaluating models are not em- ing” with formal “lifelike” entities in for- to be living systems. Whereas proponents pirically conclusive, for, by definition, the mal environments, which are then of “weak” A-Life consider models to rep- hypothetical empirical references of empirically interpreted. resent certain aspects of living phenom- these models belong to a domain This new strategy is highly promising ena, strong A-Lifers claim that the broader than the already known and with regard to the problem of the uni- phenomenology of the computational even the effectively existent. Despite the versalization of biology. However, it also environment is life in the strict sense. fact that “virtual experimentation” pro- poses new and intriguing questions, be- The model or simulacrum is considered vides some formal rigor to the method- cause it is the consequence of pure ab- a literal realization—that is to say, an ob- ology (compared to the use of theories stractions of processes taking place in ject whose phenomenology would make based on ordinary language), there re- empirical environments. In particular, I it equivalent to any natural system of the mains a problem of global empirical in- want to stress three issues: The first, corresponding empirical domain. terpretation, since, as I have mentioned, which is basically epistemological (al- Nevertheless, among those authors there is no clear referent [11]. This is one though it has ontological implications, as who regard these systems as true realiza- of the main differences between A-Life well), involves the confusion between ob- tions, the use of the term “model” is quite and classical scientific methodology, in ject and model; the second one, of a widespread (even despite the awareness which experiments and measurements, methodological nature, is the problem of its difference from the classical mean- no matter how idealized, are always per- of evaluating hypotheses (and, therefore, ing), probably because A-Life research formed or stated within the framework research programs); and the third con- and experimentation generate subse- of models that can be given a rigorous cerns the interrelation between science, quent virtual, tentative structures for empirical interpretation. philosophy and technology. methodological reasons. As a matter of Typically, an A-Life model is designed fact, then, depending on the circum- by taking as a starting point some basic stances, a computational system is inter- principles from the general theories of a THE CONFUSION BETWEEN preted sometimes as an object (ultimately, certain area of empirical biology. These OBJECT AND MODEL what is interpreted as an object is the principles are then introduced in the de- In science, a model is essentially a sym- model associated with the physical struc- sign of a computer program in which bolic construction whose structure is in- ture of the machine that sustains its exe- only low-level instructions (local rules) tended to refer to a given empirical cution [8]), at other times as a proper are made explicit, so that new patterns process. There is a wide variety of mod- model or even as a tool or methodologi- (which play the role of new rules at els, from the strictly mathematical to the cal technique mediating between the higher levels) may appear. The charac- purely conceptual, but in essence, they “true object” (natural biological systems) teristics of these patterns, however, are all try to capture or reproduce some and the “true theory” (theories of em- not known in advance by the designer. In generic feature of a given empirical do- pirical life sciences) [9]. this process, the emergence in the run- main. In biology (as in all the other tra- In short, the solution to these dilem- ning of the program in the computer of ditional empirical sciences), models are mas involves determining the ontologi- new structures (clearly distinguishable in elaborated to operatively represent em- cal status of such artificial systems. Are spatial and/or temporal terms) is fun- pirical living systems. These empirical sys- they real or virtual? What is the empiri- damental. Then, according to the afore- tems thus constitute the objects of cal referent for a computational simu- mentioned theories, some of these new reference for the models. Regardless of lacrum? B. Smith, for instance, claims patterns become hierarchically and func-
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Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/002409402760181204 by guest on 25 September 2021 A A - R tionally organized and finally become L T subject to empirical interpretation. I F The next step in this process is the E comparison of this first result with what we know of the corresponding empirical domain. As a result, the methodology consists in a continuous revision of the values of the parameters (and even of some of the actual principles according to which the original design of the model was made), depending on the degree of coherence exhibited by the results in re- lation to the phenomenology of the em- pirical domain under study (see Fig. 1). Therefore, the manifest problem is first that in A-Life computational systems, evaluation is not discernible from the in- terpretation of “emergent” patterns or processes generated in such systems, nor from the establishment of epistemologi- Fig. 2. The relation between the empirical, theoretical and computational domains in A-Life. cal criteria for selecting the primitives (© Alvaro Moreno) that define the models. So there arises the initial problem of how to set up the employed or of the set-up values for the behaviors present in the corresponding main features of the model. Here, apart initial parameters, etc.). empirical domains. All the same, the from the basic criterion of simplicity, the Nevertheless, the problem of the eval- problem of escaping mathematization usual way of proceeding is to search for uation of models goes deeper, because, might well put the actual autonomy of (sub-)models that, somehow, implicitly depending on the epistemological status A-Life as a discipline in question [16]. ensure that the assumed abstraction will given to computational systems, the ac- The attempt to answer these questions be “valid,” i.e. that the new information tual research program may vary quite takes us well beyond the strictly method- will be coherent with what happens in radically. Should we try to design “plau- ological realm, as it requires determin- well-known biological systems. The lim- sible” models (that is, computational ing the actual nature of what a model is its on simplification are set so as to avoid A-Life models that “resemble” the be- to discern (sometimes, rather than a par- results that appear trivial in the selected havior of the corresponding natural sys- ticular phenomenon in a particular em- phenomenological domain [12]. The tems) or, on the contrary, should the pirical domain, the model addresses and, aim is thus double-sided: simplicity is pur- main goal lie in some other direction, one hopes, elucidates certain computa- sued, provided that, at the same time, the such as in the search for models that ful- tional issues). At the same time, one must model is able to generate sufficient com- fill certain primarily formal criteria (for address the role that meta-theoretical plexity in the course of the simulation. example, the capacity to generate com- conceptual elements play in the design Thus, the design of a model ought to putational complexity)? Finally, in other of models, as well as the nature of the fulfill two basic requirements. On the cases, the model may be designed to seek, technical objects employed. one hand, it is important that emergent instead of prediction, to learn how a processes or structures, which may be in- given kind of biological system works. In terpreted as new data in the empirical do- such a case, higher degrees of complex- HE NTERRELATION BETWEEN main under investigation, are obtained. ity might be introduced at the micro- T I On the other hand (and in order to avoid scopic level of the model’s design [14]. SCIENCE, PHILOSOPHY AND the problem of how to determine when The problem with a purely formalist TECHNOLOGY the empirical interpretation of these new conception of A-Life (i.e. that the task of Given the nature of the problems it ad- structures and/or processes is objectively A-Life models is mainly to “unpack” and dresses, A-Life might appear closer to justified), it is necessary to design the make explicit the logical consequences philosophy than to empirical science computational experiment so that at least of their starting premises) is that A-Life and, in particular, closer to the philoso- the expected type of results can be fore- risks becoming a discipline closer to phy of biology than to biology itself. cast, and that these are specific enough mathematics than to any empirical sci- Owing to the specificity of its methodol- within each particular domain [13]. If ence. Several authors have formulated se- ogy, A-Life has to face and analyze in an only the first condition is met, the prob- rious doubts about this approach. entirely new way several important philo- lem becomes how to justify its interpre- Maynard Smith, for instance, has called sophical issues in biology, such as the de- tation; if only the second one is met, the A-Life a “science without facts,” referring bates between reductionism and vitalism, risk is that the result will be trivial. Thus, to the problem of how to assess a set of the problem of emergence, and the depending on the results obtained by computational models whose (potential) matter-form relationship [17]. This is a running the program, it will be deter- empirical references are imprecise and result of the deep entanglement of A-Life mined whether the model is valid or not, generic [15]. However, this criticism is methodology with the meta-theoretical although other elements will play a role too strong, because most A-Lifers, both (i.e. philosophical) problems of biology. in the evaluation, as in the traditional sci- in the design of their models and in the This peculiarity is not unique to A-Life, ences (for example, auxiliary theories, evaluation of their results, usually take but is shared by other computational or the adequacy of the computational tools into account the theories as well as the artificial sciences devoted to the study of
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Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/002409402760181204 by guest on 25 September 2021 A A - R L T empirical phenomena, such as AI. Re- highly significant feature of this idea is domain and of developing new concepts I garding this question, J. Casti [18] and that the interaction does not merely coherent with the body of knowledge of F E D. Lane [19] hold that the construction occur between a philosophical or meta- traditional biology, which properly stud- of models in these “sciences of surrogate scientific level and a scientific one. A new ies that domain. Both processes— worlds” requires theories about particu- technological level (constituted by the construction and interpretation—are lar empirical domains, specifically, about computational tools, with their double- deeply entangled, because A-Life re- the kinds of objects that are found in sided nature as software and hardware) search is a continuous concatenation of each of them and about how these ob- also plays a crucial role in this hermeneu- constructions, interpretations, modifica- jects relate to one another, or the types tic process. This is because computers tions, new interpretations and re- of processes that create or destroy them make possible the exploration and visu- constructions. or otherwise change their nature. The alization of a given set of work premises relevance of computational models to through the creation of virtual worlds of their corresponding empirical domains indefinite complexity [21] (see Fig. 2). CONCLUSION would be mediated by these theories, This last feature is particularly charac- If the issues are presented and under- which would constrain the interpretation teristic of the A-Life research program. stood as above, A-Life could help to over- of the models. In turn, such models aid As D. Dennett [22] has pointed out, come the gap between empirical science the analysis of these theories by provid- A-Life can be conceived as a special sort and philosophy, as each of them has tra- ing more powerful tools than ordinary of philosophy [23], which allows the cre- ditionally been conceived. In traditional language. ation and testing of complex thought ex- philosophy of science, the interaction This idea poses problems, however. periments, “kept honest by requirements under analysis involves the empirical do- First, as post-positivist philosophers of that could never be imposed on the main, the empirical theories and the science have broadly argued, the con- naked mind of a human thinker alone” meta-theories (a relationship in which cepts on which models in traditional em- [24]. That is why I consider A-Life re- technology plays a significant role only pirical sciences are constructed are also search to consist basically in the creation in the interactions between the first two). mediated by theories, in a sense similar of prosthetically controlled thought ex- In A-Life, by contrast, a new way of in- to that identified by Lane. This is why the periments of indefinite complexity. By in- terrelating empirical theories and meta- differences between these two types of creasing the capacity and precision of the theories arises, which involves the models are not stated in the terms men- human mind through these prostheses mediation of technological devices. On tioned by Lane, although it is quite true that are computers, we will be able to in- the one hand, this new connection is that the use of such virtual models does crease indefinitely the complexity of such more limited than in the traditional phi- indeed involve, and rather directly, the experiments as well. losophy of biology, since A-Life must be aforementioned meta-theoretical prob- However, the computer does not sim- restricted to conceptual issues that arise lems. The question to address is why this ply act as an extension of our conceptual in the context of implemented (compu- is so. world, as Dennett asserts; its novelty lies tational) systems; but on the other hand, Second, these models are, in principle, in the blending of concepts with com- A-Life is more rigorous and powerful, be- purely formal, even though the formula- putational technology, creating a new do- cause it uses quasi-experimental methods tion of their basic principles is inspired in main with its own ontological claims. In of validation (computational experi- a given empirical domain. As I mentioned A-Life, a set of systems generated as a re- mentation) and also because it can, in above, the difficulties of interpreting and sult of putting together human concepts principle, make the traditional range of testing A-Life models in terms of current and artifacts somehow is constituted as problems of biological meta-theories biological knowledge lie in the meta- real objects for epistemological purposes. even wider. Hence, A-Life research is theoretical implications implicit in the In other words, an ontology is founded opening up radically new perspectives, epistemological status of the entities and from an epistemological standpoint. Yet not only by bringing about profound relations that constitute such models. this happens in such a way that concepts changes in the meaning of such concepts Nevertheless, my main criterion for once embodied in the machine are trans- as experimentation, models or evalua- evaluating the usefulness of these mod- formed; they have acquired some onto- tion (of theory), but also because the sta- els is their capacity to improve our un- logical dimension and establish, in turn, tus of the philosophy of biology is clearly derstanding of the theories of the a new epistemological relationship with being modified and becoming deeply in- empirical biological world. Apparently, their creators and users. terwoven with technology. All this puts in this is a vicious circle. This is why A-Life, on the one hand, question the classical distinctions be- According to Lane, these problems constitutes an engineering activity whose tween science and philosophy and de- could be progressively resolved. On the starting point is a set of basic biological mands a more elaborate framework for one hand, the models of computational intuitions about the empirical biological proper accounts of the ever more com- sciences can improve our theories about domain. A-Life then attempts to build sys- plex and dialectical bonds between them. the corresponding empirical domains; tems capable of producing emergent and on the other hand, these theories be- functional processes by themselves. In References and Notes come essential for testing the relevance order to do so, it proceeds by creatively 1. C. Emmeche, The Garden in the Machine (Prince- of specific surrogate worlds as useful integrating different technological re- ton, NJ: Princeton Univ. Press, 1994) p. 161. models. In this way, a kind of “hermeneu- sources with theoretical developments in 2. M. Boden, “Autonomy and Artificiality,” in M. tic” circularity is established between computer science and physics. On the Boden, ed., The Philosophy of Artificial Life (Oxford, models and theories [20], since the mod- other hand, A-Life involves a process of U.K.: Oxford Univ. Press, 1996) pp. 95–108; L. Risan, els are used for the elucidation of theo- interpreting the behavior of such systems “Why Are There So Few Biologists Here?” in P. Hus- bands and I. Harvey, eds., Proceedings of the Fourth Eu- ries about the empirical world, and these with the aim of broadening the phe- ropean Conference on Artificial Life (Cambridge, MA: are then used to interpret the models. A nomenology of the empirical biological MIT Press, 1997) pp. 28–35.
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Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/002409402760181204 by guest on 25 September 2021 A A - R 3. A. Moreno. and J. Fernández, “A Vida Artificial 9. H.H. Pattee has criticized this confusion between Technical Report CSRP 378, COGS (University of L T como Projeto de Criação de uma Nova Biologia Uni- computational simulations and realizations of mate- Sussex, U.K., 1995). I versal,” in C.N. El-Hani and A.A.P. Videira, eds., O rial biological systems, arguing that the former are F que é vida? Para entender a Biologia do século XXI (Rio mere symbolic systems, whereas the latter derive their 17. At the same time, A-Life research programs al- E de Janeiro, Brazil: Editorial Relume Dumará, 2000) capacities precisely from the autonomously gener- lows the reformulation of such questions. pp. 257–271. ated symbolic constraint in material systems. See 18. Casti, Would-Be Worlds [11]. H.H. Pattee, “Simulations, Realizations and Theories 4. A. Moreno and K. Ruiz-Mirazo, “Metabolism and of Life,” in Langton [6] pp. 63–77. 19. D. Lane, “Models and Aphorisms,” Complexity 1, the Problem of Its Universalization,” BioSystems 49, No. 2, pp. 9–13 (1995). No. 1, 45–61 (1999). 10. B.C. Smith, On the Origin of Objects (Cambridge, MA: MIT Press, 1996) pp. 75, 359. 20. G.B. Kleindorfer, L. O’Neil and R. Ganeshan, 5. N. Block, “What Is Functionalism?” in N. Block, “Validation in Simulation: Various Positions in the 11. J. Casti, Would-Be Worlds: How Simulation Is Chang- ed., Readings in the Philosophy of Psychology, Vol. 1 Philosophy of Science,” Management Science 44, No. ing the Frontiers of Science (New York: John Wiley, 1997) (Cambridge, MA: Harvard Univ. Press, 1980) 8, 1087–1099 (1998). pp. 171–184; E. Sober, “Learning from Functional- pp. 187–188. J. Casti, “The Computer as a Labora- ism: Prospects for Strong Artificial Life,” in C. Lang- tory,” Complexity 4, No. 5, pp. 12–14 (1999). 21. Although there are, of course, various kinds of ton, C. Taylor, D. Farmer and S. Rassmusen, eds., technological tools within A-Life (such as robots or 12. In fact, one of the main objectives of a model in Artificial Life II (Redwood City, CA: Addison-Wesley, other devices), the most important and prevalent way A-Life is to show something new not only in a given 1992) pp. 749–765. of developing and testing models in this research phenomenological domain but also in the domain field is through computers. Therefore, my discussion of the internal correlations of the systems under 6. C. Langton, “Artificial Life,” in C. Langton, ed., focuses on them. Artificial Life (Redwood City, CA: Addison-Wesley, study. 1989) pp. 1–47. 22. D. Dennett, “Artificial Life as Philosophy,” Arti- 13. Another problem to be avoided is that of ambi- ficial Life 1, No. 3, 291–292 (1994). 7. Emmeche [1] p. 163. guity, i.e. too-generic results congruent with a very large range of phenomena. 23. Other authors showing enthusiasm for the future 8. E.T. Olson, for instance, has argued against the of A-Life as a philosophy include E.W. Bonabeau and 14. D. Gross and R. Strand, “Can Agent-Based Mod- “immateriality” of those “virtual organizations,” as- G. Theraulaz, “Why Do We Need Artificial Life?” Ar- els Assist Decisions on Large-Scale Practical Prob- serting that one could actually see them as real phys- tificial Life 1, No. 3, 303–325 (1994). lems? A Philosophical Analysis,” Complexity 5, No. 6, ical systems if, instead of looking at the computer 26–33 (2000). program in abstract terms, one considers the pat- 24. Dennett [22] p. 291. terns of electrons which materially support the exe- 15. Quoted in J. Horgan, “From Complexity to Per- cution of that program. See E.T. Olson, “The plexity,” Scientific American (June 1995) pp. 104–109. Ontological Basis of Strong Artificial Life,” Artificial Alvaro Moreno is a philosopher of science, Life 3, No. 1, 29–39 (1997). Yet this argument misses 16. Miller, for example, has claimed that A-Life can whose specialty is the philosophy of biology and the point, because the material structures that sup- only become a fully scientific discipline through its port the operational level of computer simulations are en- integration into the field of theoretical biology. See complex systems at large: he has written a book tirely passive, as their intrinsic dynamics is completely G. Miller, “Artificial Life as Theoretical Biology: How and many articles about the methodology and constrained. See Moreno and Ruiz-Mirazo [4]. to Do Real Science with Computer Simulation,” epistemology of artificial life.
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