On the Convergence of Fictitious Play: A Decomposition Approach. (arXiv:2205.01469v1 [cs.GT])

Web: http://arxiv.org/abs/2205.01469

Fictitious play (FP) is one of the most fundamental game-theoretical learning
frameworks for computing Nash equilibrium in $n$-player games, which builds the
foundation for modern multi-agent learning algorithms. Although FP has provable
convergence guarantees on zero-sum games and potential games, many real-world
problems are often a mixture of both and the convergence property of FP has not
been fully studied yet. In this paper, we extend the convergence results of FP
to the combinations of such games and beyond. Specifically, …

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