• Corpus ID: 245650754

# Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning

@article{Tang2022OperatorDQ,
title={Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning},
author={Ziyang Tang and Yihao Feng and Qiang Liu},
journal={ArXiv},
year={2022},
volume={abs/2201.00236}
}
• Published 1 January 2022
• Computer Science
• ArXiv
Reinforcement learning (RL) has drawn increasing interests in recent years due to its tremendous success in various applications. However, standard RL algorithms can only be applied for single reward function, and cannot adapt to an unseen reward function quickly. In this paper, we advocate a general operator view of reinforcement learning, which enables us to directly approximate the operator that maps from reward function to value function. The benefit of learning the operator is that we can…

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