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Artificial Intelligence and Spontaneous Collusion

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  • Martino Banchio
  • Giacomo Mantegazza

Abstract

We develop a tractable model for studying strategic interactions between learning algorithms. We uncover a mechanism responsible for the emergence of algorithmic collusion. We observe that algorithms periodically coordinate on actions that are more profitable than static Nash equilibria. This novel collusive channel relies on an endogenous statistical linkage in the algorithms' estimates which we call spontaneous coupling. The model's parameters predict whether the statistical linkage will appear, and what market structures facilitate algorithmic collusion. We show that spontaneous coupling can sustain collusion in prices and market shares, complementing experimental findings in the literature. Finally, we apply our results to design algorithmic markets.

Suggested Citation

  • Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
    • Handle: RePEc:arx:papers:2202.05946
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    References listed on IDEAS

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    Cited by:

    1. Pranjal Rawat, 2023. "Designing Auctions when Algorithms Learn to Bid: The critical role of Payment Rules," Papers 2306.09437, arXiv.org.
    2. Eshwar Ram Arunachaleswaran & Natalie Collina & Sampath Kannan & Aaron Roth & Juba Ziani, 2024. "Algorithmic Collusion Without Threats," Papers 2409.03956, arXiv.org, revised Dec 2024.
    3. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    4. Inkoo Cho & Noah Williams, 2024. "Collusive Outcomes Without Collusion," Papers 2403.07177, arXiv.org.
    5. Maximilian Schaefer, 2022. "On the Emergence of Cooperation in the Repeated Prisoner's Dilemma," Papers 2211.15331, arXiv.org, revised Feb 2023.
    6. Olivier Compte, 2023. "Q-learning with biased policy rules," Papers 2304.12647, arXiv.org, revised Oct 2023.
    7. Ludovico Crippa & Yonatan Gur & Bar Light, 2022. "Equilibria in Repeated Games under No-Regret with Dynamic Benchmarks," Papers 2212.03152, arXiv.org, revised Jul 2023.

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