AAMAS 2024 Imperfect-Information Card Games Competition

Mahjong, Texas hold’em and Bridge are three popular strategical board games worldwide. Each game has plenty of advanced players, let alone the amateurs. These games often have complex game rules with enormously large state space, rendering it challenging for designing a strong AI player. There have been various attempts to solve these classic card games. In Mahjong, Suphx developed by Microsoft Research Asia is the first AI system that outperforms most top human players using deep reinforcement learning methods; in the Heads-Up No-Limit Texas Hold’em game, AlphaHoldem manages to reach the level of professional human players through self-playing; in the multi-player Texas Hold’em game, Pluribs is trained to play a strong strategy that is capable of consistently defeating elite human professionals; in the game of Bridge, there exists a well-known computer bridge software Wbridge5 using a Monte-Carlo search in the bidding process and a few attempts adopting deep reinforcement learning techniques.

In order to further advance the research in the turn-based card game AI, we propose the AAMAS 2024 Imperfect-Information Card Games Competition and hold the competition on the Jidi platform. This competition aims to encourage the development of card game AI under imperfect-information setting when facing various opponent tactics.