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arXiv · 2504.16222

Nash Equilibrium Learning In Large Populations With First-Order Payoff Modifications

Matthew S. Hankins·Jair Certório·Tzuyu Jeng·Nuno C. Martins
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Abstract

We establish Nash equilibrium learning in large populations of noncooperative, strategic agents. Our analysis considers the broadest class to date of payoff mechanisms with first-order modifications, capable of modeling bounded rationality and anticipatory effects, averaging, or Pad\'{e} delay approximations. We propose a framework that, for the first time, combines two nonstandard system-theoretic passivity notions. Our results hold for discontinuous best response dynamics alongside continuous learning rules, significantly extending prior work.

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BibTeXRIS

Matthew S. Hankins, Jair Certório, Tzuyu Jeng, Nuno C. Martins. 2025-04-22. Nash Equilibrium Learning In Large Populations With First-Order Payoff Modifications. https://doi.org/10.1109/lcsys.2025.3573119

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