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A framework for the functional analysis of behaviour

Published online by Cambridge University Press:  04 February 2010

Alasdair I. Houston  and
John M. McNamara
Alasdair I. Houston
Affiliation:
Department of Zoology, Edward Grey Institute, University of Oxford, Oxford 0X1 3PS, England
John M. McNamara
Affiliation:
School of Mathematics, University of Bristol, Bristol BS8 1TYI, England
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Abstract

We present a general framework for analyzing the contribution to reproductive success of a behavioural action. An action may make a direct contribution to reproductive success, but even in the absence of a direct contribution it may make an indirect contribution by changing the animal's state. We consider actions over a period of time, and define a reward function that characterizes the relationship between the animal's state at the end of the period and its future reproductive success. Working back from the end of the period using dynamic programming, the optimal action as a function of state and time can be found. The procedure also yields a measure of the cost, in terms of future reproductive success, of a suboptimal action. These costs provide us with a common currency for comparing activities such as eating and drinking, or eating and hiding from predators. The costs also give an indication of the robustness of the conclusions that can be drawn from a model. We review how our framework can be used to analyze optimal foraging decisions in a stochastic environment. We also discuss the modelling of optimal daily routines and provide an illustration based on singing to attract a mate. We use the model to investigate the features that can produce a dawn song burst in birds. State is defined very broadly so that it includes the information an animal has about its environment. Thus, exploration and learning can be included within the framework.

Keywords

adaptationbehavioural ecologycausal explanationdynamic optimizationevolutionforagingfunctional explanationlearningmatchingmaximizationpopulation biologyreproductive successsociobiology
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 11 , Issue 1 , March 1988 , pp. 117 - 130
Copyright
Copyright © Cambridge University Press 1988

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