Tabletop Game

Tabletop games are increasingly serving as a testbed for advancements in artificial intelligence, particularly in multi-agent reinforcement learning and robotics. Current research focuses on developing algorithms and models, including deep neural networks and integer linear programming, to address challenges like object detection, pose estimation, and manipulation for robotic interaction with tabletop environments, as well as creating AI agents capable of playing complex tabletop games. This work contributes to both fundamental AI research and practical applications, such as improving robotic dexterity and creating more engaging and accessible gaming experiences through AI assistance.