Verified probabilistic policies for deep reinforcement learning
Deep reinforcement learning is an increasingly popular technique for synthesising policies to control an agent’s interaction with its environment. There is also growing interest in formally verifying that such policies are correct and execute safely. Progress has been made in this area by building o...
Main Authors: | , |
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Format: | Conference item |
Language: | English |
Published: |
Springer
2022
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