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Coevolution of cognition and cooperation in structured populations under reinforcement learning

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  • Mastrandrea, Rossana
  • Boncinelli, Leonardo
  • Bilancini, Ennio

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

  • Mastrandrea, Rossana & Boncinelli, Leonardo & Bilancini, Ennio, 2024. "Coevolution of cognition and cooperation in structured populations under reinforcement learning," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:chsofr:v:182:y:2024:i:c:s0960077924003515
    DOI: 10.1016/j.chaos.2024.114799
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