Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation

NeurIPS 2016 Tejas D. KulkarniKarthik R. NarasimhanArdavan SaeediJoshua B. Tenenbaum

Learning goal-directed behavior in environments with sparse feedback is a major challenge for reinforcement learning algorithms. The primary difficulty arises due to insufficient exploration, resulting in an agent being unable to learn robust value functions... (read more)

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