MAPLE: Multi-State Aggregated Policy Evaluation for AlphaZero in Imperfect-Information Games 事件

MAPLE: Multi-State Aggregated Policy Evaluation for AlphaZero in Imperfect-Information Games arXiv:2605.24139v1 Announce Type: new Abstract: Imperfect-information games (IIGs) are challenging, as players must make decisions without fully observing the true game state. While AlphaZero has achieved remarkable success in perfect-information games, extending it to IIGs remains difficult. Existing search-based approaches, such as Perfect Information Monte Carlo (PIMC), suffer from strategy fusion, w