Continuous control with deep reinforcement learning

9 Sep 2015Timothy P. LillicrapJonathan J. HuntAlexander PritzelNicolas HeessTom ErezYuval TassaDavid SilverDaan Wierstra

We adapt the ideas underlying the success of Deep Q-Learning to the continuous action domain. We present an actor-critic, model-free algorithm based on the deterministic policy gradient that can operate over continuous action spaces... (read more)

PDF Abstract


Evaluation Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.