'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

The first Hors d'Oeuvres, Anyone? event at the Association for the Advancement of Artificial Intelligence Mobile Robot Competition was held in 1997. Five teams entered their robotic waiters into the contest. After a preliminary round to judge the safety of the robots, the robots served conference attendees at the opening reception of the Fourteenth National Conference on Artificial Intelligence.

To remain competitive, enterprises must become increasingly agile and integrated across their functions. Enterprise models play a critical role in this integration, enabling better designs for enterprises, analysis of their performance, and management of their operations. This article motivates the need for enterprise models and introduces the concepts of generic and deductive enterprise models. It reviews research to date on enterprise modeling and considers in detail the Toronto virtual enterprise effort at the University of Toronto.

Details about program does not provide any scholarship information, please contact AAAI at these programs will also be mailed to funds, and is designed for local fss@aaai.org

This article gives an overview of two recent events on the validation and verification of knowledge-based systems: (1) the 1997 European Symposium on the Verification and Validation of Knowledge-Based Systems (EUROVAV-97) and (2) the Four-teenth National Conference on Artificial Intelligence Workshop on the Verification and Validation of Knowledge- Based Systems. To give an integrated view of current research issues in this field, we organized this article along thematic lines, unifying the reports of the two separate meetings. Our report focuses on the trends that we think will be important in the near future in this field.

The robot uses a layered Intelligence (AAAI-97). Twenty-one robotic architecture for integrating planning and teams participated, making this the largest action. It differs from the usual approach of robot exhibition ever. See figure 1 for a photo interfacing a planner to a reactive system in a of the exhibition participants. Since the first layered architecture because the reactive system Mobile Robot Competition and Exhibition at is replaced with a different kind of action AAAI-92, the exhibition has served to demonstrate system.

Book review of "How the Mind Works, Steven Pinker, W. W. Norton & Co., New York, 1997, 660 pp., $29.90, ISBN 0-393- 04535-8.

Second, team's software was able to find, recognize, Because the camera and the arm are on about 200 pounds. An edge-detection algorithm equipped with 2 rings of 16 sonar sensors. The camera was calibrated system is used on board the robot. Positioned to Pick Up every time it was moved. When the robot was trying edge in 3D space relative to the robot.

This article describes a milestone in our research efforts toward the real robot competition in RoboCup. We participated in the middle-size league at RoboCup-97, held in conjunction with the Fifteenth International Joint Conference on Artificial Intelligence in Nagoya, Japan. The most significant features of our team, TRACKIES, are the application of a reinforcement learning method enhanced for real robot applications and the use of an omnidirectional vision system for our goalie that can capture a 360-degree view at any instant in time. The method and the system used are shown with competition results.

Please send papers to: AAAI-99--American Association for Artificial Intelligence 445 Burgess Drive Menlo Park, CA 94025-3442 Registration and call clarification inquiries (only) may be sent to ncai@aaai.org.