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Incorporating rules for responding into evolutionary games

Author

Listed:
  • John M. McNamara

    (School of Mathematics, University of Bristol)

  • Catherine E. Gasson

    (School of Biological Sciences, University of Bristol)

  • Alasdair I Houston

    (School of Biological Sciences, University of Bristol)

Abstract

Evolutionary game theory1,2 is concerned with the evolutionarily stable outcomes of the process of natural selection. The theory is especially relevant when the fitness of an organism depends on the behaviour of other members of its population. Here we focus on the interaction between two organisms that have a conflict of interest. The standard approach to such two-player games is to assume that each player chooses a single action and that the evolutionarily stable action of each player is the best given the action of its opponent. We argue that, instead, most two-player games should be modelled as involving a series of interactions in which opponents negotiate the final outcome. Thus we should be concerned with evolutionarily stable negotiation rules rather than evolutionarily stable actions. The evolutionarily stable negotiation rule of each player is the best rule given the rule of its opponent. As we show, the action chosen as a result of the negotiation is not the best action given the action of the opponent. This conclusion necessitates a fundamental change in the way that evolutionary games are modelled.

Suggested Citation

  • John M. McNamara & Catherine E. Gasson & Alasdair I Houston, 1999. "Incorporating rules for responding into evolutionary games," Nature, Nature, vol. 401(6751), pages 368-371, September.
  • Handle: RePEc:nat:nature:v:401:y:1999:i:6751:d:10.1038_43869
    DOI: 10.1038/43869
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    Citations

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    Cited by:

    1. Jiabin Wu, 2020. "Labelling, homophily and preference evolution," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(1), pages 1-22, March.
    2. Ingela Alger & Laurent Lehmann, 2023. "Evolution of Semi-Kantian Preferences in Two-Player Assortative Interactions with Complete and Incomplete Information and Plasticity," Dynamic Games and Applications, Springer, vol. 13(4), pages 1288-1319, December.
    3. Jessica Meade & Ki-Baek Nam & Jin-Won Lee & Ben J Hatchwell, 2011. "An Experimental Test of the Information Model for Negotiation of Biparental Care," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-7, May.
    4. Alger, Ingela & Lehmann, Laurent & Weibull, Jörgen W., 2015. "Does evolution lead to maximizing behavior?," IAST Working Papers 15-20, Institute for Advanced Study in Toulouse (IAST).
    5. John M McNamara & Alasdair I Houston & Olof Leimar, 2021. "Learning, exploitation and bias in games," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-14, February.
    6. Erol Akçay & Joan Roughgarden, 2009. "The Perfect Family: Decision Making in Biparental Care," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-10, October.
    7. Ennio Bilancini & Leonardo Boncinelli & Jiabin Wu, 2016. "The Interplay of Cultural Aversion and Assortativity for the Emergence of Cooperation," Center for Economic Research (RECent) 121, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    8. Daiping Wang & Wenyuan Zhang & Shuai Yang & Xiang-Yi Li Richter, 2023. "Sex differences in avian parental care patterns vary across the breeding cycle," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    9. Tina A Barbasch & Rebecca Branconi & Robin Francis & Madison Pacaro & Maya Srinivasan & Geoffrey P Jones & Peter M Buston, 2021. "Negotiations over parental care: a test of alternative hypotheses in the clown anemonefish," Behavioral Ecology, International Society for Behavioral Ecology, vol. 32(6), pages 1256-1265.
    10. Ennio Bilancini & Leonardo Boncinelli & Jiabin Wuz, 2016. "The Interplay of Cultural Aversion and Assortativity for the Emergence of Cooperation," Department of Economics 0084, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    11. Yamaguchi, Sachi & Iwasa, Yoh, 2015. "Phenotype adjustment promotes adaptive evolution in a game without conflict," Theoretical Population Biology, Elsevier, vol. 102(C), pages 16-25.

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