Learning to Understand Goal Specifications by Modelling Reward

ICLR, 2019.

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Other Links: arxiv.org|dblp.uni-trier.de

Abstract:

Recent work has shown that deep reinforcement-learning agents can learn to follow language-like instructions from infrequent environment rewards. However, this places on environment designers the onus of designing language-conditional reward functions which may not be easily or tractably implemented as the complexity of the environment ...More

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