Agent-Based Foraging or When Imperfect Unbiased knowledge Yields Systematic Deviation from Ideally Rational Outcomes

Animal foraging regimes are standardly modeled as economic systems, for which standard economic modeling and its assumptions are apt. Patch selection foraging models are a case in point. There, the ideal free distribution (IFD) model has canonically served to explain and predict equilibrium distribution of foragers across patches. We investigate patch selection under assumptions of imperfect information on the part of the forager agents. In a first regime, agents’ perceptions (upon which they act) are drawn from Gaussian distributions with a common standard deviation and mean equal to the true value of the productivity of the patch in question. In a second regime, agents’ perceptions are modeled using Weber’s law of just noticeable differences (JND), a biologically and psychologically well-established model, one arguably more realistic than simple Gaussian error. The paper finds that both regimes yield similar systematic, stable, non-equilibrium deviations from the IFD. In particular, the distributions of agents across patches, while stable and not in equilibrium, systematically under sample higher productivity patches and over sample lower productivity patches, a phenomenon that has been observed in the field and reported in the literature on animal foraging. The paper sketches an analytic proof of why this should be the case. If the main finding of the paper—that imperfect knowledge yields systematic deviations from ideal rationality behavior—can be shown to generalize well to other economic contexts, then the methods of agent-based modeling combined with fundamental biological and psychological principles may be material for yielding yet more satisfactory, empirically warranted accounts of social behavior than the incumbent idealizations.