DouDizhu AI

DouDizhu AI research focuses on developing artificial intelligence agents capable of mastering the complex, three-player card game DouDizhu, which involves both cooperation and competition under imperfect information. Current research emphasizes improving existing deep reinforcement learning models, such as those based on Monte Carlo methods and neural networks (including residual networks), by incorporating techniques like opponent modeling and "perfect information distillation" to enhance strategic decision-making and training efficiency. These advancements demonstrate significant progress in tackling challenging multi-agent games with imperfect information, contributing to broader understanding of AI in complex strategic environments and potentially informing the development of more robust AI systems for other domains.