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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Bibliographic Details
Main Authors: Hailan Yang, Shengze Li, Xinhai Xu, Xunyun Liu, Zhuxuan Meng, Yongjun Zhang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9360826/