This paper studies a population of agents, each of whom can be either an Altruist or an Egoist. Altruists confer benefits on others at a cost to themselves. Altruism is thus a strictly dominated strategy and cannot survive if agents are rational best-responders. We assume that agents choose their actions by imitating others who earn high payoffs. We also assume that interactions between agents are local, so that each agent a ects (and is affected by) only his neighbors. Altruists can survive in such a world if they are grouped together, so that the benefits of Altruism are enjoyed primarily by other Altruists, who then earn relatively high payo s and are imitated. The addition of mutations to the model threatens this survival by allowing such groups to be invaded by mutant Egoists. However, mutations can also be inimical to Egoists, by removing the Altruists which Egoists exploit,and the net effect of mutations is to ensure that Altruists survive.
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Paper provided by ESRC Centre on Economics Learning and Social Evolution in its series ELSE working papers with number
005.
Find related papers by JEL classification: C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Itzhak Gilboa & David Schmeidler, 1992.
"Case-Based Decision Theory,"
Discussion Papers
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[Downloadable!]
Itzhak Gilboa & David Schmeidler, 1993.
"Case-Based Optimization,"
Discussion Papers
1039, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
[Downloadable!]