Torsell, Christian (2026) Egalitarianism and Evolution. [Preprint]
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Abstract
An agent is inequity averse if their preferences reflect a distaste for material inequality. Inequity aversion is of both scientific and philosophical interest. In behavioral economics, it is central to popular explanations of ``anomalous'' behavior in resource-division games. In social and political philosophy, it is of interest because it embodies an egalitarian approach to distributive bargaining. We use the indirect evolutionary approach, an extension of standard evolutionary game theory, to consider whether inequity aversion can survive competition with selfishness under natural dynamics like social learning and Darwinian evolution. In particular, we study evolution in populations playing a variant of the Nash demand game, a popular model of bargaining. Unlike related extant work, we assume that individuals play the base game repeatedly within their lifetimes, learning as they do. The central result is that, under a broad range of assumptions about the evolutionary dynamics and the initial population state, inequity aversion goes to fixation in populations comprising both inequity averse and selfish agents. Incorporating learning turns out to be crucial to the evolutionary result. The model thus supports two conclusions. First, egalitarian attitudes can survive and proliferate in competition with selfish ones. Second, in applying the indirect evolutionary approach, integrating intragenerational learning can influence the evolutionary dynamics in important ways.
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| Item Type: | Preprint | ||||||
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| Keywords: | evolutionary game theory, inequity aversion, egalitarianism, bargaining, fairness, learning | ||||||
| Subjects: | Specific Sciences > Psychology > Evolutionary Psychology Specific Sciences > Biology > Evolutionary Theory General Issues > Computer Simulation Specific Sciences > Economics General Issues > Game Theory Specific Sciences > Cognitive Science > Learning and Memory |
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| Depositing User: | Christian Torsell | ||||||
| Date Deposited: | 06 Feb 2026 13:42 | ||||||
| Last Modified: | 06 Feb 2026 13:42 | ||||||
| Item ID: | 28135 | ||||||
| Subjects: | Specific Sciences > Psychology > Evolutionary Psychology Specific Sciences > Biology > Evolutionary Theory General Issues > Computer Simulation Specific Sciences > Economics General Issues > Game Theory Specific Sciences > Cognitive Science > Learning and Memory |
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| Date: | 5 February 2026 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/28135 |
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