We describe a stochastic model of an animal exploring and foraging within a
n uncertain environment. Behaviour is determined not by an optimizing algor
ithm but by fuzzy systems using linguistic rules derived from the informati
on primacy hypothesis which stresses the importance of continual informatio
n gathering under conditions of uncertainty. In the model, the animal's hun
ger 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 whethe
r 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 the
se two aspects of a given location. In complex and changing environments fr
esh information is likely to be more accurate than old information and cons
equently our model gives most weight to recently gathered information. All
sources of uncertainty are reduced by visiting locations and gathering fres
h information. The model is successful in simulating results from experimen
ts investigating such phenomena as: spontaneous alternation; patrolling; th
e effects of hunger on the variability of learnt responses; latent learning
; contrafreeloading; and behaviour following changes in food availability.
(C) 2001 The Association for the Study of Animal Behaviour.