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Noise free multi-armed bandit game

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2016) 9618 412-423
DOI: 10.1007/978-3-319-30000-9_32
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Abstract

We study the loss version of adversarial multi-armed bandit problems with one lossless arm. We show an adversary’s strategy that forces any player to suffer K − 1 − O(1/T) loss where K is the number of arms and T is the number of rounds.

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Nakamura, A., Helmbold, D. P., & Warmuth, M. K. (2016). Noise free multi-armed bandit game. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9618, pp. 412–423). Springer Verlag. https://doi.org/10.1007/978-3-319-30000-9_32

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