QUOTA: The Quantile Option Architecture for Reinforcement Learning
0209 industrial biotechnology
02 engineering and technology
DOI:
10.1609/aaai.v33i01.33015797
Publication Date:
2019-08-28T07:48:44Z
AUTHORS (2)
ABSTRACT
In this paper, we propose the Quantile Option Architecture (QUOTA) for exploration based on recent advances in distributional reinforcement learning (RL). In QUOTA, decision making is based on quantiles of a value distribution, not only the mean. QUOTA provides a new dimension for exploration via making use of both optimism and pessimism of a value distribution. We demonstrate the performance advantage of QUOTA in both challenging video games and physical robot simulators.
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