Turning Uncertainty into Confidence in Strategic Games: Reinforcement Learning–Guided Adaptive-Weighted MCTS
In imperfect-information decision environments, the decision-making process often suffers from low search efficiency and limited strategic performance due to the high complexity of hidden-state interactions. To address these challenges, this paper pro
Authors
- Shi Shen (ORCID: https://orcid.org/0000-0001-8392-6068)
- Jiehong Wu (ORCID: https://orcid.org/0000-0002-0851-3009)
- Xuanming Cao (ORCID: https://orcid.org/0009-0003-2415-9809)
- Cunqian Yu (ORCID: https://orcid.org/0000-0002-3450-2231)
Institutions
- Shenyang Aerospace University (CN)
Publication Details
- Published
- 2025-10-16
- DOI
- https://doi.org/10.22541/au.176060366.68637329/v1
- Primary Topic
- Auction Theory and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00