How to miss data? Reinforcement learning for environments with high observation cost

Abstract

We present a self-tuning RL agent that learns to adjust the accuracy of the samples when the observation cost is an intrinsic part of the environment.

Publication
ICML Workshop on The Art of Learning with Missing Values

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