Admissible policy teaching through reward design
We study reward design strategies for incentivizing a reinforcement learning agent to adopt a policy from a set of admissible policies. The goal of the reward designer is to modify the underlying reward function cost-efficiently while ensuring that any approximately optimal deterministic policy unde...
Main Authors: | , , , |
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Format: | Conference item |
Language: | English |
Published: |
Association for the Advancement of Artificial Intelligence
2022
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