Abstract

Maximization theory, which is borrowed from economics, provides techniques for predicing the behavior of animals - including humans. A theoretical behavioral space is constructed in which each point represents a given combination of various behavioral alternatives. With two alternatives - behavior A and behavior B - each point within the space represents a certain amount of time spent performing behavior A and a certain amount of time spent performing behavior B. A particular environmental situation can be described as a constraint on available points (a circumscribed area) within the space. Maximization theory assumes that animals always choose the available point with the highest numerical value. The task of maximization theory is to assign to points in the behavioral space values that remain constant across various environmental situations; as those situations change, the point actually chosen is always the one with the highest assigned value.