Re-exploration of ε-greedy in deep reinforcement learning
This paper presents re-exploration as a method for improving the existing method for balancing the exploration/exploitation problem integral to reinforcement learning. The proposed method uses a ε-greedy method called “decreasing epsilon,” which reiterate the method after a certain period of episode...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/96174/ http://dx.doi.org/10.1007/978-981-16-4803-8_27 |
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