Inclusive Fitness and the Maximizing-Agent Analogy

British Journal for the Philosophy of Science:axw003 (2016)
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Abstract

ABSTRACT In social evolution theory, biological individuals are often represented on the model of rational agents, that is, as if they were ‘seeking’ to maximize their own reproductive success. In the 1990s, important criticisms of this mode of thinking were made by Brian Skyrms and Elliott Sober, who both argued that ‘rational agent’ models can lead to incorrect predictions when there are positive correlations between individuals’ phenotypes. In this article, I argue that one model of rational choice—namely, Savage’s model —can actually be vindicated in evolutionary biology, provided that the pay-offs are computed in inclusive fitness terms. I also show that the use of this model is better avoided when pay-offs are non-additive, or when certain causal influences affect the outcome of natural selection. The result is a partial rehabilitation of this mode of thinking, conditional on both the additivity of the pay-off structure and the absence of any form of manipulation or coercion. _1_ Introduction _2_ When Natural Selection and Rational Deliberation Part Ways _3_ A Simple Solution: Redefining the Pay-offs in Inclusive Fitness Terms _4_ Sober on Inclusive Fitness Maximization _5_ Inclusive Fitness with Non-additive Pay-offs _6_ Causal Influences and the Savage– Hamilton Model _6.1_ Reciprocity and partner choice _6.2_ Coercion and manipulation _7_ Conclusion Appendix

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Hamilton meets causal decision theory.Johannes Martens - 2019 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 77:101187.

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References found in this work

Counterfactuals.David K. Lewis - 1973 - Malden, Mass.: Blackwell.
Counterfactuals.David Lewis - 1973 - Foundations of Language 13 (1):145-151.
Counterfactuals.David Lewis - 1973 - Tijdschrift Voor Filosofie 36 (3):602-605.
The Foundations of Statistics.Leonard J. Savage - 1954 - Synthese 11 (1):86-89.

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