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Adapting to Conflict: Equilibrium Structure and Adaptive Learning in Harmonic Games

NeurIPS 2026 · Bandits and online learning › Online convex optimization and games · approach: Last-iterate convergence in games

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Studies equilibrium structure and adaptive learning dynamics in harmonic games, a robust generalization of zero-sum games that is invariant under strategic equivalence.

Problem

Zero-sum games can fail to capture conflict even in simple settings, and harmonic games, a more robust model of opposed interests, have a structure whose equilibria and learning behavior are not well understood.

Approach

Harmonic games generalize zero-sum competition beyond pairwise settings while staying invariant under strategic equivalence; the paper characterizes the equilibrium structure of odd-dimensional harmonic games and studies adaptive learning in them.

Key results

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