Algorithmic collusion: Genuine or spurious?

Emilio Calvano, Giacomo Calzolari, Vincenzo Denicolò and Sergio Pastorello

International Journal of Industrial Organization, 2023, vol. 90, issue C

Abstract: Reinforcement-learning pricing algorithms sometimes converge to supra-competitive prices even in markets where collusion is impossible by design or cannot be an equilibrium outcome. We analyze when such spurious collusion may arise, and when instead the algorithms learn genuinely collusive strategies, focusing on the role of the rate and mode of exploration.

Keywords: Artificial intelligence; reinforcement learning; collusion; exploration (search for similar items in EconPapers)
JEL-codes: D43 D83 L13 L41 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:indorg:v:90:y:2023:i:c:s0167718723000541

DOI: 10.1016/j.ijindorg.2023.102973

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