Researchers and technology developers from the National Aeronautics and Space Administration (NASA), other government agencies, academia, and industry recently met in Pasadena, California, to take stock of past and current work and future challenges in the application of AI to highly autonomous systems. The meeting was catalyzed by new opportunities in developing autonomous spacecraft for NASA and was in part a celebration of the fictional birth year of the HAL-9000 computer.

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.

In this article, we describe the milestone of our research efforts in our work for the RoboCup middle-size league competition. Reinforcement learning in applying it to real robot applications; we then give our method of coping with these has recently been receiving increased attention issues in the context of RoboCup. Finally, we as a method for robot learning with little or no show our system and the experimental results a priori knowledge and a higher capability for of RoboCup-97. The robot senses the current state First, we follow the explanation of Q-learning of the environment and selects an action. For a more thorough treatment, Based on the state and the action, the environment see Watkins and Dayan (1992).

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.

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.

Points were awarded for picking up objects of a specific type (ball, cube, or moving squiggle ball) and specific color (figure 2). Penalty points were deducted for he Mars Pathfinder Mission, featuring for the Find-Life-on-Mars event. The general colliding with rocks, placing an object in the concept was to have the robots locate, collect, wrong door, and traveling within the danger and deliver a variety of "life forms," zones. We also specified penalties for modifying including both stationary and moving objects. the lander, although no group took advantage Technically, the event was designed to highlight of this option. No other modification of mobile manipulation, object recognition, the environment was allowed.

The Association for the Advancement of Artificial Intelligence Spring Symposium on Interactive and Mixed-Initiative Decision-Theoretic Systems was held at Stanford University from 23-25 March 1998. The symposium attracted approximately 30 researchers from around the world. Topics discussed included incremental model construction, user interaction, explanation generation, and applications.

In July 1997, the Sixth Annual Association for the Advancement of Artificial Intelligence (AAAI) Mobile Robot Competition and Exhibition was held. The competition consisted of four new events: (1) Find Life on Mars; (2) Find the Remote; (3) Home Vacuum; and (4) Hors d'Oeuvres, Anyone? The robot exhibition was the largest in AAAI history. This article presents the history, motivation, and contributions for the event.

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.