Proceedings of the Annual Meeting of the Cognitive Science Society

Models in cognitive science often postulate that individuals maintain complex representations of their environment when simpler explanations, based on simple behaviors interacting with each other and environmental constraints, would suffice. As an example, I consider representational approaches to animal behavior (e.g., Gallistel, 1990; Myerson and Miezin, 1980), which posit that complex group behavior results from complex representations of events within the central nervous systems of individual animals. For example, ducks feeding from two food sources distribute themselves proportionately to the density of food available at each source. This phenomenon, probability matching, is typically explained by attributing representations of the density of food available at each source within the central nervous system (CNS) of each duck. Are such complex representations required to explain this phenomenon? I will compare the results of two simulations of probability matching in groups. In one, individuals maintain and update representations of food available at each source. Although probability matching emerges, the organisms exhibit various unrealistic behaviors. In the second, each individual follows simple behavioral rules but has no representation of the food density at each source. Probability matching emerges and the behavior observed is more realistic than that in the first simulation. This adds to demonstrations in other domains that complexity at one level of analysis need not result from complexity at lower levels (e.g., Resnick, 1994; Sigmund, 1993).