RISKY THEORIES - THE EFFECTS OF VARIANCE ON FORAGING DECISIONS

Citation
A. Kacelnik et M. Bateson, RISKY THEORIES - THE EFFECTS OF VARIANCE ON FORAGING DECISIONS, American zoologist, 36(4), 1996, pp. 402-434
Citations number
112
Categorie Soggetti
Zoology
Journal title
ISSN journal
00031569
Volume
36
Issue
4
Year of publication
1996
Pages
402 - 434
Database
ISI
SICI code
0003-1569(1996)36:4<402:RT-TEO>2.0.ZU;2-P
Abstract
This paper concerns the response of foraging animals to variability in rate of gain, or risk. Both the empirical and theoretical literatures relevant to this issue are reviewed. The methodology and results from fifty-nine studies in which animals are required to choose between fo raging options differing in the variances in the rate of gain availabl e are tabulated, We found that when risk is generated by variability i n the amount of reward, animals are most frequently risk-averse and so metimes indifferent to risk, although in some studies preference depen ds on energy budget. In contrast, when variability is in delay to rewa rd, animals are universally risk-prone. A range of functional, descrip tive and mechanistic accounts for these findings is described, none of which alone is capable of accommodating all aspects of the data. Risk -sensitive foraging theory provides the only currently available expla nation for why energy budget should affect preference. An information- processing model that incorporates Weber's law provides the only gener al explanation for why animals should be risk-averse with variability in amount and risk-prone with delay. A theory based on the mechanisms of associative learning explains quantitative aspects of risk-pronenes s for delay; specifically why the delay between choice and reward shou ld have a stronger impact on preference than delays between the reward and subsequent choice. It also explains why animals should appear to commit the ''fallacy of the average,'' maximising the expected ratio o f amount of reward over delay to reward when computing rates rather th an the ratio of expected amount over expected delay. We conclude that only a fusion of functional and mechanistic thinking will lead to prog ress in the understanding of animal decision making.