Safer Deep RL with Shallow MCTS: A Case Study in Pommerman

10 Apr 2019Bilal KartalPablo Hernandez-LealChao GaoMatthew E. Taylor

Safe reinforcement learning has many variants and it is still an open research problem. Here, we focus on how to use action guidance by means of a non-expert demonstrator to avoid catastrophic events in a domain with sparse, delayed, and deceptive rewards: the recently-proposed multi-agent benchmark of Pommerman... (read more)

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