Using Natural Language for Reward Shaping in Reinforcement Learning
IJCAI, pp. 2385-2391, 2019.
Recent reinforcement learning (RL) approaches have shown strong performance in complex domains such as Atari games, but are often highly sample inefficient. A common approach to reduce interaction time with the environment is to use reward shaping, which involves carefully designing reward functions that provide the agent intermediate rew...More
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