Model-Ensemble Trust-Region Policy Optimization

  title={Model-Ensemble Trust-Region Policy Optimization},
  author={Thanard Kurutach and Ignasi Clavera and Yan Duan and Aviv Tamar and Pieter Abbeel},
Model-free reinforcement learning (RL) methods are succeeding in a growing number of tasks, aided by recent advances in deep learning. However, they tend to suffer from high sample complexity which hinders their use in real-world domains. Alternatively, model-based reinforcement learning promises to reduce sample complexity, but tends to require careful tuning and, to date, it has succeeded mainly in restrictive domains where simple models are sufficient for learning. In this paper, we analyze… CONTINUE READING


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