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  • title: Best of Both Worlds Policy Optimization
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            Best of Both Worlds Policy Optimization
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            Best of Both Worlds Policy Optimization

            Jul 25, 2023

            Speakers

            CD

            Christoph Dann

            Speaker · 0 followers

            CW

            Chen-Yu Wei

            Speaker · 0 followers

            JZ

            Julian Zimmert

            Speaker · 0 followers

            About

            Policy optimization methods are popular reinforcement learning algorithms in practice and recent works have build theoretical foundation for them by proving $\sqrt{T}$ regret bounds even when the losses are adversarial. Such bounds are tight in the worst case but often overly pessimistic. In this work, we show that by carefully designing the regularizer, bonus terms, and learning rates, one can achieve a more favorable $\text{polylog}(T)$ regret bound when the losses are stochastic, without sacr…

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            I2

            ICML 2023

            Account · 615 followers

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