Relating reinforcement learning performance to classification performance

Abstract

We prove a quantitative connection between the expected sum of rewards of a policy and binary classification performance on created subproblems. This connection holds without any unobservable assumptions (no assumption of independence, small mixing time, fully observable states, or even hidden states) and the resulting statement is independent of the number… (More)
DOI: 10.1145/1102351.1102411

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