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Found 2 papers, 1 papers with code
Diverse Projection Ensembles for Distributional Reinforcement Learning
In contrast to classical reinforcement learning, distributional reinforcement learning algorithms aim to learn the distribution of returns rather than their expected value.
Safe Continuous Control with Constrained Model-Based Policy Optimization
Further, we provide theoretical and empirical analyses regarding the implications of model-usage on constrained policy optimization problems and introduce a practical algorithm that accelerates policy search with model-generated data.
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