- With the rapid development of artificial intelligence, robotics, and unmanned systems, intelligent systems are gradually moving beyond perception, recognition, and instruction following toward cognitive understanding and autonomous decision-making in real-world scenarios. Complex open environments are often dynamic, incomplete, uncertain, and collaborative, which places higher demands on environmental understanding, goal reasoning, action selection, and adaptive capabilities. Therefore, establishing effective connections among perception, cognition, and action, and developing decision-making mechanisms based on task requirements and environmental feedback, has become an important issue in intelligent systems research.
This organized session focuses on ”Embodied Cognition and Decision-Making.“ It aims to discuss cognitive modeling, situational understanding, task reasoning, decision planning, behavior control, and system coordination in the process of interaction between agents and their environments. From the perspectives of fundamental theories, key methods, and application-oriented exploration, the session will examine how intelligent systems understand scenes, reason about goals, select actions, and form closed-loop feedback in complex environments. The session is expected to provide a platform for academic exchange in robotics, unmanned systems, intelligent control, and human-machine collaboration, and to promote the development of intelligent systems from passive response toward active understanding and autonomous decision-making.
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