A model for the evolution of reinforcement learning in fluctuating games

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Serval ID
serval:BIB_AC26C188AEA1
Type
Article: article from journal or magazin.
Collection
Publications
Title
A model for the evolution of reinforcement learning in fluctuating games
Journal
Animal Behaviour
Author(s)
Dridi S., Lehmann L.
ISSN
1095-8282 (ISSN)
ISSN-L
0003-3472
Publication state
Published
Issued date
2015
Volume
104
Pages
87-114
Language
english
Abstract
Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.
Keywords
evolution of cognition, evolutionarily stable learning rules, exploration-exploitation trade-off, repeated games, social interactions, trial-and-error learning
Web of science
Open Access
Yes
Create date
06/11/2017 11:39
Last modification date
20/08/2019 16:16
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