Social Phenomena Emerging by Self-Organisation in a Competitive, Virtual World ('Domworld')

Social phenomena emerging by self-organisation in a competitive, virtual world (‘DomWorld’). Charlotte K. Hemelrijk Department of Information Technology and Anthropological Institute and Museum, University of Zürich, Switzerland [email protected] Abstract This essay explains how spatial structuring among competitive agents in an agent-based model leads to all kinds of behavioural patterns that are not represented in the behavioural rules of the agents. These phenomena resemble those observed in the real world, and thus, the model provides us with explanations and hypotheses that are more parsimonious than those of the conventional ‘top-down’, rationalistic view. This I show by means of five examples of a model called ‘DomWorld’ in which agents inhabit a virtual, homogeneous world and are equipped only with rules for two activities, namely to group and to perform competitive interactions. The first example demonstrates the origination of reciprocation of help in fights (yet the agents lack all moralistic feelings and have no motivation to help others in fights), and the second shows reduction of aggression when agents get familiarised with others (yet agents lack all internal mechanism to do so). The third reveals the phenomenon of spatial centrality of dominant agents (yet agents have no preference for any location within the group). The fourth example demonstrates the increase of dominance reversals between the sexes when grouping is cohesive (yet the agents lack all coalitionary tendency) and the fifth shows increased male ‘tolerance’ during periods of sexual attraction (in spite of the absence of any motivation to exchange). In sum, spatial positioning and dominance interactions among nearby, simple agents may lead to interesting social phenomena by self-organisation. 1 Introduction Patterns of social behaviour may arise by self-organisation through self-reinforcing interactions. Such reinforcing interactions are observed everywhere, even in traffic jams (Resnick 1994). Nevertheless, only very few studies address the question how social behaviour may arise by self- organisation. The reason is that this approach runs counter to the usual explanation according to which each separate behavioural act is supposed to be genetically inherited or intentional. This disregard of the process of self-organisation is a consequence of the so-called ‘top-down’ approach, in which investigators first observe behaviour, and then subdivide it into independent traits, for each of which they draw up separate explanations. Because different researchers tend to investigate different features, possible interconnections among traits are overlooked. Thus, the top- down procedure keeps our attention away from emergent patterns that arise from the complicated feedback between interrelated variables. Feedback mechanisms are best understood by using the opposite route, the ‘bottom-up’ modelling approach. In such models we emphasise processes and dynamics. These models consist, for instance, in an artificial world inhabited by virtual creatures that interact with nearby others and are equipped with a minimum of ‘realistic’ rules. To detect the regularities that materialise from the model, we need behavioural definitions and categories similar to those used in ethological studies of real animals. By tracing patterns of interactions over time, we discover how social structure unfolds by self-organisation from a complex feedback process between characteristics of individuals, their interactions and their developing social organisation. Structures that originate in this way are neither intentional nor genetically inherited (e.g. see Hogeweg 1988). I shall illustrate this with five examples that arise in my model from the feedback between the spatial positioning of group-living, virtual agents and their self-reinforcing competitive interactions. These emergent effects are (1) reciprocation of support in fights, (2) decline of aggression, (3) spatial centrality of dominants, (4) female dominance over males and (5) male ‘tolerance’ of females. These examples show how the result of the process of self-organisation leads to more parsimonious hypotheses than the ‘top-down’ procedure. It is, therefore, important to supplement conventional studies on social behaviour with the approach explained in the present paper. 2 The Dominance World (DomWorld) A summary of the model may suffice; for a more complete description see Hemelrijk (1999b; 2000). The model is inspired by that of Hogeweg (1988). It is based on only a small number of essentials of social life: It consists in a homogeneous virtual world inhabited by agents that are provided with only two tendencies: 1) to group (right half of Figure 1) and 2) to perform dominance interactions (left part of Figure 1). Why agents group (whether this is to avoid predators or because of resources being clumped) is not specified and irrelevant to the model. The same holds for dominance interactions. They reflect competition for resources (such as food and mates), but these resources are not specified. A dominance interaction takes place only if another agent is very near, in its personal space (PersSpace). The likelihood that an agent initiates an aggressive interaction increases with its chance to defeat its opponent (Hemelrijk 2000). The agent’s capacity to be victorious (i.e. its dominance) depends, in line with ample empirical evidence, on the self- reinforcing effects of winning (and losing): Winning a fight increases the probability of winning the next time. After victory the dominance value of the victorious agent increases and that of the defeated one is reduced by the same amount. When, unexpectedly, an agent defeats a higher- ranking opponent, the dominance values of both opponents are changed with a greater amount than when the agent, as expected, conquers a lower-ranking opponent (conform to detailed behavioural studies on bumble bees by Honk & Hogeweg 1981). In this way the model allows for rank reversals. After a fight, the winner chases the opponent and the defeated agent flees. The sexes differ only in fighting capacity: ‘Male’ agents start with a higher initial dominance value and are characterised by a higher intensity of attack than ‘female’ agents. To show the effects of winning and losing as clearly as possible, all agents of the same sex are identical at the start. Groups consist usually of 5 males and 5 females. The behaviour of the agents is analysed by means of behavioural units and statistical methods similar to those used for observing real animals. Figure 1: Flow chart for the behavioural rules of agents that are not attracted to another type (sex) 2 3 The emergence of reciprocation of support in conflicts. In the real world, individuals sometimes join in fights between two opponents. This is called ‘supporting’ behaviour (behaviour of individual C in Figure 2) and it seems sometimes to be reciprocated. From observing such ‘reciprocation’ among primates, investigators conclude that ‘moralistic’ intentions and record keeping of acts given and received underlie this behaviour (de Waal 1982). In DomWorld, however, reciprocation of support in fights arises in spite of the fact that agents are unable to perceive and return debts and lack all motivation to help others and all ability to keep records of acts (Hemelrijk 1996). Figure 2: Schematic representation of ‘support’: 1) fight between A and B, next 2) C attacks B. The behaviour of C is interpreted as ‘support’ for A. Instead, the so-called supporting behaviour and its reciprocation arises from the spatial con- figuration of the agents (Hemelrijk 1997). When one of two nearby agents (say ‘A’) chases away a third agent (‘B’), the third one may by accident come within the range of attack of the nearby agent (‘C’). In this way agents ‘A’ and ‘C’ take turns in chasing away the same victim ‘B’ and thus ‘reciprocate’ each other’s ‘support’. Because co-operating agents are more disturbed and distracted by others in dense than in loose groups, reciprocation occurs less often and bouts of alternating ‘support‘ are shorter in dense than loose groups. That crowding prevents cooperation is not very remarkable, but looseness of groups is itself the result of a parameter setting for a large domain of aggression. Thus, the counter-intuitive, unexpected conclusion from the virtual world - and a readily testable, hypothesis for the real world - is that more aggressive agents are more co-operative. Such co-operation by turn taking, as found in the model, is, from the point of view of an ob- server, similar to the game theoretical ‘Tit-for-Tat Strategy’ (Axelrod & Hamilton 1981). However, this similarity invalidates rather than supports the assumptions behind this theory. In the game theoretical framework co-operation is assumed to evolve on the basis of arbitrary pay-off (in terms of fitness). Cooperation is studied as an isolated feature, unconnected to other behavioural activities, despite the common-sense knowledge that natural selection operates on complete individuals and not on separate traits. The present essay, in contrast, neither deals with evolutionary processes, nor with pay-offs from cooperation. Instead, cooperation is viewed as a direct consequence of the intertwined effects of local competition and the gathering of agents. 4 Decrease of aggression In many animal species, it is often seen that, when unfamiliar individuals are put together, initially dominance relations are unclear and aggression at first flares up and then, when a dominance hierarchy becomes manifest in

Load more