AAAI presented the AAAI-04 workshop program on July 25-26, 2004 in San Jose, California. This program included twelve workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were as follows: (1) Adaptive Text Extraction and Mining; (2) Agent Organizations: Theory and Practice; (3) Anchoring Symbols to Sensor Data; (4) Challenges in Game AI; (5) Fielding Applications of Artificial Intelligence; (6) Forming and Maintaining Coalitions in Adaptive Multiagent Systems; (7) Intelligent Agent Architectures: Combining the Strengths of Software Engineering and Cognitive Systems; (8) Learning and Planning in Markov Processes -- Advances and Challenges; (9) Semantic Web Personalization; (10) Sensor Networks; (11) Spatial and Temporal Reasoning; and (12) Supervisory Control of Learning and Adaptive Systems.

AAAI presented the AAAI-04 workshop program on July 25-26, 2004 in San Jose, California. This program included twelve workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were as follows: (1) Adaptive Text Extraction and Mining; (2) Agent Organizations: Theory and Practice; (3) Anchoring Symbols to Sensor Data; (4) Challenges in Game AI; (5) Fielding Applications of Artificial Intelligence; (6) Forming and Maintaining Coalitions in Adaptive Multiagent Systems; (7) Intelligent Agent Architectures: Combining the Strengths of Software Engineering and Cognitive Systems; (8) Learning and Planning in Markov Processes -- Advances and Challenges; (9) Semantic Web Personalization; (10) Sensor Networks; (11) Spatial and Temporal Reasoning; and (12) Supervisory Control of Learning and Adaptive Systems.

ISIS: An Explicit Model of Teamwork at RobotCup-97

's performance in is driven by's development was driven by the Using Further aspects of multiagent agents could not always quickly locate and agent and team modeling. With respect to learning, as well as arenas of agent and intercept the ball or maintain awareness of teamwork, our previous work was based on team modeling (particularly to recognize positions of teammates and opponents. It then enables team members to make any decisions. Instead, all the decision Yaser Al-Onaizan, Ali Erdem, autonomously reason about coordination making rests with the higher level, Gal A. Kaminka, Stacy C. Marsella, and communication in teamwork, providing implemented in the Given its domain architecture, which takes into account the independence, it also enables reuse across recommendations made by the lower level. 's teamwork reasoning is currently test domain given its substantial also implemented in