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5.3 Example 2 - Communication, Learning and the El Farol Bar Problem

5.3.4 The emergence of heterogeneity


In contrast to Arthur's model, this model shows the clear development of different roles
*1.

By the end of the run described above agent-3 and agent-1 had developed a stand-alone repetoire of strategies which largely ignored what other agents said. Agent-3 had settled on what is called a mixed strategy in game theory, namely that it would go about two-thirds of the time in a randomly determined way, while agent-1 relied on largely deterministic forecasting strategies.

The other three agents had developed what might be called social strategies. Agent-2 seemed to have come to rely on `tricking' agent-4 into going when it was not, which explains the gradual accumulation of `NOT's in the example gene described above. Agent-4 has come to rely (at least somewhat) on what agent-2 says and likewise agent-5 uses what agent-4 says (although both mix this with other methods including a degree of randomness).

Thus although all agents were indistinguishable at the start of the run in terms of their resources and computational structure, they evolved not only different models but also very distinct strategies and roles.

One conclusion to be drawn from this model is that, if only global communication is allowed, and internal models have limited expressiveness, then it might be preventing the emergence of heterogeneity. Or, to put it another way, endowing agents with the ability to make real social distinctions and (implicit or explicit) models of each other enables socially situated behaviour to emerge. This phenomena does not emerge in Arthur's original model..

Such a conclusion marries well with other models which enable local and specific communication between its agents (e.g. [1]) and goes some way to addressing the criticisms in [13]. For a more philosophical analysis of the nature of the social processes taking place in this model see [10].


Modelling Bounded Rationality In Agent-Based Simulations using the Evolution of Mental Models - 17 MAR 98
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