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Let’s be Honest: An Optimal No-Regret Framework for Zero-Sum Games

ICML 2018 • Ehsan Asadi Kangarshahi • Ya-Ping Hsieh • Mehmet Fatih Sahin • Volkan Cevher

We revisit the problem of solving two-player zero-sum games in the decentralized setting. We propose a simple algorithmic framework that simultaneously achieves the best rates for honest regret as well as adversarial regret, and in addition resolves the open problem of removing the logarithmic terms in convergence to the value of the game... (read more)

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