Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring

17 Jun 2020Taira TsuchiyaJunya HondaMasashi Sugiyama

We investigate finite stochastic partial monitoring, which is a general model for sequential learning with limited feedback. While Thompson sampling is one of the most promising algorithms on a variety of online decision-making problems, its properties for stochastic partial monitoring have not been theoretically investigated, and the existing algorithm relies on a heuristic approximation of the posterior distribution... (read more)

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