2019
DOI: 10.48550/arxiv.1909.07373
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Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space

Abstract: This paper proposes a novel deep reinforcement learning architecture that was inspired by previous tree structured architectures which were only useable in discrete action spaces. Policy Prediction Network offers a way to improve sample complexity and performance on continuous control problems in exchange for extra computation at training time but at no cost in computation at rollout time. Our approach integrates a mix between model-free and model-based reinforcement learning. Policy Prediction Network is the … Show more

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