An information primacy model of exploratory and foraging behaviour

We describe a stochastic model of an animal exploring and foraging within an uncertain environment. Behaviour is determined not by an optimizing algorithm but by fuzzy systems using linguistic rules derived from the information primacy hypothesis which stresses the importance of continual information gathering under conditions of uncertainty. In the model, the animal's hunger increases steadily over time and is reduced by visiting locations that may contain varying amounts of food. Uncertainty arises from three sources: (1) location novelty or ambiguity, that is, the animal is uncertain whether it has visited the same location before; (2) variation in the amounts of food in a given location; and (3) the recency of information concerning these two aspects of a given location. In complex and changing environments fresh information is likely to be more accurate than old information and consequently our model gives most weight to recently gathered information. All sources of uncertainty are reduced by visiting locations and gathering fresh information. The model is successful in simulating results from experiments investigating such phenomena as: spontaneous alternation; patrolling; the effects of hunger on the variability of learnt responses; latent learning; contrafreeloading; and behaviour following changes in food availability.