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Some Considerations on Learning to Explore via Meta-Reinforcement Learning - 2018

Some Considerations On Learning To Explore Via Meta-Reinforcement Learning

Research Paper on Some Considerations On Learning To Explore Via Meta-Reinforcement Learning

Research Area:  Machine Learning

Abstract:

We consider the problem of exploration in meta reinforcement learning. Two new meta reinforcement learning algorithms are suggested: E-MAML and ERL2. Results are presented on a novel environment we call Krazy World and a set of maze environments. We show E-MAML and ERL2 deliver better performance on tasks where exploration is important.

Keywords:  
Meta-Reinforcement Learning
Machine Learning
Deep Learning

Author(s) Name:  Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

Journal name:  Artificial Intelligence

Conferrence name:  

Publisher name:  arXiv:1803.0111

DOI:  1803.01118

Volume Information: