No Internal Regret via Neighborhood Watch


Dean Foster, Alexander Rakhlin ;
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, PMLR 22:382-390, 2012.


We present an algorithm which attains O(\sqrtT) internal (and thus external) regret for finite games with partial monitoring under the local observability condition. Recently, this condition has been shown by Bartok, Pal, and Szepesvari (2011) to imply the O(\sqrtT) rate for partial monitoring games against an i.i.d. opponent, and the authors conjectured that the same holds for non-stochastic adversaries. Our result is in the affirmative, and it completes the characterization of possible rates for finite partial-monitoring games, an open question stated by Cesa-Bianchi, Lugosi, and Stoltz (2006). Our regret guarantees also hold for the more general model of partial monitoring with random signals.

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