Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Bradly Stadie; Ge Yang; Rein Houthooft; Xi Chen; Yan Duan; Yuhuai Wu; Pieter Abbeel; Ilya Sutskever

ICLR 2018workshop151 citations

Some Considerations on Learning to Explore via Meta-Reinforcement Learning

Bradly Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

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.

reinforcement learningrlexplorationmeta learningmeta reinforcement learningcuriosity

BibTeX

@misc{
stadie2018some,
title={Some Considerations on Learning to Explore via Meta-Reinforcement Learning},
author={Bradly Stadie and Ge Yang and Rein Houthooft and Xi Chen and Yan Duan and Yuhuai Wu and Pieter Abbeel and Ilya Sutskever},
year={2018},
url={https://openreview.net/forum?id=Skk3Jm96W},
}