Coevolution of cognition and cooperation in structured populations under reinforcement learning

Rossana Mastrandrea, Leonardo Boncinelli and Ennio Bilancini

Papers from arXiv.org

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.

Date: 2023-06, Revised 2024-03
New Economics Papers: this item is included in nep-cbe, nep-evo, nep-gth and nep-net
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Journal Article: Coevolution of cognition and cooperation in structured populations under reinforcement learning (2024)
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