4 papers
No-Regret Strategy Solving in Imperfect-Information Games via Pre-Trained Embedding
Yanchang Fu, Shengda Liu, Pei Xu +1
High-quality information set abstraction remains a core challenge in solving large-scale imperfect-information extensive-form games (IIEFGs)--such as no-limit Texas Hold'em--where…
KrwEmd: Revising the Imperfect-Recall Abstraction from Forgetting Everything
Yanchang Fu, Qiyue Yin, Shengda Liu +2
Excessive abstraction is a critical challenge in hand abstraction-a task specific to games like Texas hold'em-when solving large-scale imperfect-information games, as it impairs AI…
Beyond Outcome-Based Imperfect-Recall: Higher-Resolution Abstractions for Imperfect-Information Games
Yanchang Fu, Qiyue Yin, Shengda Liu +2
Hand abstraction is crucial for scaling imperfect-information games (IIGs) such as Texas Hold'em, yet progress is limited by the lack of a formal task model and by evaluations that…
Constructive Conflict-Driven Multi-Agent Reinforcement Learning for Strategic Diversity
Yuxiang Mai, Qiyue Yin, Wancheng Ni +2
In recent years, diversity has emerged as a useful mechanism to enhance the efficiency of multi-agent reinforcement learning (MARL). However, existing methods predominantly focus o…