Efficient Searching With MCTS and Imitation Learning: A Case Study in Pommerman
Pommerman is a popular reinforcement learning environment because it imposes several challenges such as sparse and deceptive rewards and delayed action effects. In this paper, we propose an efficient reinforcement learning approach that uses a more efficient Monte Carlo tree search combined with act...
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| Autors principals: | , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IEEE
2021-01-01
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| Col·lecció: | IEEE Access |
| Matèries: | |
| Accés en línia: | https://ieeexplore.ieee.org/document/9360826/ |
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