Policy Gradient Methods for Reinforcement Learning with Function Approximation and Action-Dependent Baselines

Philip S. Thomas; Emma Brunskill

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arXiv · 1706.06643

Policy Gradient Methods for Reinforcement Learning with Function Approximation and Action-Dependent Baselines

Philip S. Thomas·Emma Brunskill

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Abstract

We show how an action-dependent baseline can be used by the policy gradient theorem using function approximation, originally presented with action-independent baselines by (Sutton et al. 2000).

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Philip S. Thomas, Emma Brunskill. 2017-06-20. Policy Gradient Methods for Reinforcement Learning with Function Approximation and Action-Dependent Baselines. https://arxiv.org/abs/1706.06643

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