Resource-constrained Amazons chess decision framework integrating large language models and graph attention

ArXi:2603.10512v1 Announce Type: new Artificial intelligence has advanced significantly through the development of intelligent game-playing systems, providing rigorous testbeds for decision-making, strategic planning, and adaptive learning. However, resource-constrained environments pose critical challenges, as conventional deep learning methods heavily rely on extensive datasets and computational resources.