Large-Scale Study of Curiosity-Driven Learning

international conference on learning representations, 2019.

Cited by: 279|Views198
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Abstract:

Reinforcement learning algorithms rely on carefully engineering environment rewards that are extrinsic to the agent. However, annotating each environment with hand-designed, dense rewards is not scalable, motivating the need for developing reward functions that are intrinsic to the agent. Curiosity is a type of intrinsic reward function w...More

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