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      The evolution of shame and guilt

      research-article
      1 , 2 , 3 , 4 , *
      PLoS ONE
      Public Library of Science

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          Abstract

          Shame and guilt seem to be two synonymous moral emotions but actually lead to contrasting human behaviors or behavioral tendencies. Shame drives people to hide or deny their wrongdoings while guilt drives people to amend their mistakes. How shame and guilt evolved in humans is still obscure. Here we present a computer model featured with reciprocal altruism and gregarious lifestyle for studying this question. We tested ten different strategies in our model and the pairwise contests show that shame-driven-hiding strategy can dominate the other strategies such as tit-for-tat and Pavlov in more than half of parameter combinations. The mathematical analysis of our model demonstrates that shame-driven-hiding strategy is an evolutionary stable strategy within a group as long as hiding can let an individual evade the retaliations to his wrongdoings. However, the problem of hiding is that it reduces an individual’s social circle, i.e. living in a smaller group. Our analysis also shows that guilt-driven-amending strategy can outperform shame-driven-denying strategy at both individual and group levels if the cooperative behavior is sustainable within a group ( b/( b- c) < T/ n). Thus, we propose that shame is more adaptive at the individual level while guilt is more advantageous in the context of intergroup competition.

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          The evolution of cooperation

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            The evolution of cooperation.

            Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individuals occur on a probabilistic basis, a model is developed based on the concept of an evolutionarily stable strategy in the context of the Prisoner's Dilemma game. Deductions from the model, and the results of a computer tournament show how cooperation based on reciprocity can get started in an asocial world, can thrive while interacting with a wide range of other strategies, and can resist invasion once fully established. Potential applications include specific aspects of territoriality, mating, and disease.
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              A strategy of win-stay, lose-shift that outperforms tit-for-tat in the Prisoner's Dilemma game.

              The Prisoner's Dilemma is the leading metaphor for the evolution of cooperative behaviour in populations of selfish agents, especially since the well-known computer tournaments of Axelrod and their application to biological communities. In Axelrod's simulations, the simple strategy tit-for-tat did outstandingly well and subsequently became the major paradigm for reciprocal altruism. Here we present extended evolutionary simulations of heterogeneous ensembles of probabilistic strategies including mutation and selection, and report the unexpected success of another protagonist: Pavlov. This strategy is as simple as tit-for-tat and embodies the fundamental behavioural mechanism win-stay, lose-shift, which seems to be a widespread rule. Pavlov's success is based on two important advantages over tit-for-tat: it can correct occasional mistakes and exploit unconditional cooperators. This second feature prevents Pavlov populations from being undermined by unconditional cooperators, which in turn invite defectors. Pavlov seems to be more robust than tit-for-tat, suggesting that cooperative behaviour in natural situations may often be based on win-stay, lose-shift.

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 July 2018
                2018
                : 13
                : 7
                : e0199448
                Affiliations
                [1 ] Institute of Neuroscience, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
                [2 ] State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, P. R. China
                [3 ] MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, P. R. China
                [4 ] Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, P. R. China
                University of Waterloo, CANADA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-3745-0473
                Article
                PONE-D-17-35512
                10.1371/journal.pone.0199448
                6040729
                29995883
                fca5f70a-cd6c-4b42-bb35-9ddebce57d6c
                © 2018 Libing Shen

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 October 2017
                : 7 June 2018
                Page count
                Figures: 3, Tables: 2, Pages: 11
                Funding
                The author received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Behavior
                Biology and Life Sciences
                Psychology
                Emotions
                Social Sciences
                Psychology
                Emotions
                Computer and Information Sciences
                Computer Modeling
                Physical Sciences
                Mathematics
                Applied Mathematics
                Game Theory
                Prisoner's Dilemma
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Evolutionary Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Evolutionary Algorithms
                Research and Analysis Methods
                Computational Techniques
                Evolutionary Computation
                Evolutionary Algorithms
                Biology and Life Sciences
                Behavior
                Prosocial Behavior
                Altruistic Behavior
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Social Cognition
                Prosocial Behavior
                Altruistic Behavior
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Social Cognition
                Prosocial Behavior
                Altruistic Behavior
                Social Sciences
                Psychology
                Cognitive Psychology
                Social Cognition
                Prosocial Behavior
                Altruistic Behavior
                Biology and Life Sciences
                Psychology
                Social Psychology
                Social Cognition
                Prosocial Behavior
                Altruistic Behavior
                Social Sciences
                Psychology
                Social Psychology
                Social Cognition
                Prosocial Behavior
                Altruistic Behavior
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Computer and Information Sciences
                Computer Applications
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