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New adaptive punishment method boosts cooperation in mixed-motive games

Researchers have developed a new method called Adaptive Punishment for Cooperation (APC) to encourage cooperation in mixed-motive games. APC dynamically adjusts the intensity and probability of punishment based on the severity of defection, aiming to reduce costly and ineffective punishment. This approach uses a defection awareness module to assess defection severity, guided by game rewards. Theoretical and empirical results demonstrate APC's effectiveness in promoting cooperation in iterated public goods games and other social dilemmas, outperforming existing methods. AI

影响 Introduces a novel strategy for fostering cooperation in multi-agent systems, potentially improving outcomes in scenarios involving self-interested agents.

排序理由 The cluster contains an academic paper detailing a new method for multi-agent systems. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Min Tang, Fanqi Kong, Linyuan L\"u, Xue Feng ·

    Adaptive Punishment for Cooperation in Mixed-Motive Games

    arXiv:2605.24516v1 Announce Type: cross Abstract: Mixed-motive scenarios are ubiquitous in real-world multi-agent interactions, where self-interested agents often defect for immediate rewards, overlooking the potential of altruistic cooperation to improve long-term gains and coll…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Xue Feng ·

    Adaptive Punishment for Cooperation in Mixed-Motive Games

    Mixed-motive scenarios are ubiquitous in real-world multi-agent interactions, where self-interested agents often defect for immediate rewards, overlooking the potential of altruistic cooperation to improve long-term gains and collective welfare. Peer punishment can deter defectio…