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Coevolution of cognition and cooperation in structured populations under reinforcement learning

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  • Rossana Mastrandrea
  • Leonardo Boncinelli
  • Ennio Bilancini

Abstract

We study the evolution of behavior under reinforcement learning in a Prisoner's Dilemma where agents interact in a regular network and can learn about whether they play one-shot or repeatedly by incurring a cost of deliberation. With respect to other behavioral rules used in the literature, (i) we confirm the existence of a threshold value of the probability of repeated interaction, switching the emergent behavior from intuitive defector to dual-process cooperator; (ii) we find a different role of the node degree, with smaller degrees reducing the evolutionary success of dual-process cooperators; (iii) we observe a higher frequency of deliberation.

Suggested Citation

  • Rossana Mastrandrea & Leonardo Boncinelli & Ennio Bilancini, 2023. "Coevolution of cognition and cooperation in structured populations under reinforcement learning," Papers 2306.11376, arXiv.org, revised Mar 2024.
    • Handle: RePEc:arx:papers:2306.11376
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    References listed on IDEAS

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    3. Stephan Jagau & Matthijs van Veelen, 2017. "A general evolutionary framework for the role of intuition and deliberation in cooperation," Nature Human Behaviour, Nature, vol. 1(8), pages 1-6, August.
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