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When it's Good to Feel Bad: an evolutionary model of guilt and apology

Rosenstock, Sarita and O'Connor, Cailin (2018) When it's Good to Feel Bad: an evolutionary model of guilt and apology. [Preprint]

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Abstract

We use techniques from evolutionary game theory to analyze the conditions under which guilt can provide individual �fitness bene�fits, and so evolve. In particular, we focus on the bene�fits of guilty apology. We consider models where actors err in an iterated prisoner's dilemma and have the option to apologize. Guilt either improves the trustworthiness of apology, or imposes a cost on actors who apologize. We analyze the stability and likelihood of evolution of such a `guilt-prone' strategy against cooperators, defectors, grim-triggers, and individuals who o�ffer fake apologies, but continue to defect. We fi�nd that in evolutionary models guilty apology is more likely to evolve in cases where actors interact repeatedly over long periods of time, where the costs of apology are low or moderate, and where guilt is hard to fake. Researchers interested in naturalized ethics, and emotion researchers, can employ these results to assess the plausibility of fuller accounts of the evolution of guilt.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Rosenstock, Saritarosensts@uci.edu
O'Connor, Cailincailino@uci.edu
Keywords: guilt, evolutionary game theory, prisoner's dilemma, iterated prisoner's dilemma, apology, moral emotions, naturalized ethics
Subjects: Specific Sciences > Biology > Evolutionary Theory
General Issues > Ethical Issues
Specific Sciences > Psychology/Psychiatry
Depositing User: Dr. Cailin O'Connor
Date Deposited: 10 Mar 2016 21:56
Last Modified: 11 Feb 2018 22:27
Item ID: 11958
Journal or Publication Title: Frontiers in Robotics and AI
Subjects: Specific Sciences > Biology > Evolutionary Theory
General Issues > Ethical Issues
Specific Sciences > Psychology/Psychiatry
Date: February 2018
URI: http://philsci-archive.pitt.edu/id/eprint/11958

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