All inquiries should include your travel support for students who are registration area. Now Exempt from applicants must have fulfilled your lab's research efforts to be the volunteer and reporting requirements California Sales Tax shown to a large portion of the AI for previous awards. This year, Recent California legislation required community. California that can be run in parallel on several who submit a letter of recommendation Senate Bill 89 (Chapter 461, screens. Please do not send tapes of a from a faculty supervisor in lieu Statutes of 1991)-signed by the governor particular project or lecture but, of a paper, student authors from foreign at press time-provides AAAI rather, tapes that present broad institutions, and foreign scholars.

I survey four viewpoints about what AI is. I describe a program exhibiting AI as one that can change as a result of interactions with the user. Such a program would have to process hundreds or thousands of examples as opposed to a handful. Because AI is a machine's attempt to explain the behavior of the (human) system it is trying to model, the ability of a program design to scale up is critical. Researchers need to face the complexities of scaling up to programs that actually serve a purpose. The move from toy domains into concrete ones has three big consequences for the development of AI. First, it will force software designers to face the idiosyncrasies of its users. Second, it will act as an important reality check between the language of the machine, the software, and the user. Third, the scaled-up programs will become templates for future work. For a variety of reasons, some of which I discuss one of the following four things: (1) AI means in this article, the newly formed Institute magic bullets, (2) AI means inference engines, for the Learning Sciences has been concentrating (3) AI means getting a machine to do something its efforts on building high-quality you didn't think a machine could do educational software for use in business and (the "gee whiz" view), and (4) AI means elementary and secondary schools. In the two having a machine learn.

Intelligence (AAAI) hopes that these This year's conference featured a new A talk united by a set of related research This year's program represented an by Jim Green0 addressed modeling issues. Constraint this approach is not seen There was time to interact Reasoning and Component Technologies as often today. Where is it session following each set of presentations. Highlights from the program focused on a presentation on among the accepted papers. A panel entitled "How Long which ran for two consecutive days Until the Household Robot: The For the first time, Innovative Applications during the conference. The emergence State of the Art in Robotics" featured in Artificial Intelligence (IAAI) of the forum Planning, Perception, speakers from industry and Carnegie presentations and AI Online interactive and Robotics reflected a recent trend Mellon's Robotic Institute, who panels were presented concurrently in Planning, with videotapes and a live robot providing an impressive demonstration Perception, and Robotics included demonstration.

Task-specific architectures are a growing area of expert system research. Evaluation is one task that is required in many problem-solving domains. This article describes a task-specific, domain-independent architecture for candidate evaluation. I discuss the task-specific architecture approach to knowledge-based system development. Next, I present a review of candidate evaluation methods that have been used in AI and psychological modeling, focusing on the distinction between discrete truth table approaches and continuous linear models. Finally, I describe a task-specific expert system shell, which includes a development environment (Ceved) and a run-time consultation environment (Ceval). This shell enables nonprogramming domain experts to easily encode and represent evaluation-type knowledge and incorporates the encoded knowledge in performance systems.

AI research is conducted at a number of academic and research units at the Georgia Institute of Technology. Some of this research is basic in nature, and some has an applied character to it. This article briefly describes basic AI research in the College of Computing at Georgia Tech.

A memorial tribute to AI researcher Jonathan King who died of cancer in 1991.

The Board of Directors the address given here.

A workshop on defeasible reasoning with specificity was held under the arch in St. Louis during April 1989, with support from AAAI and McDonnell Douglas, and the assistance of Rockwell Science Center Palo Alto and the Department of Computer Science of Washington University.

The Spring Symposium on Knowledge-based Environments for Teaching and Learning focused on the use of technology to facilitate learning, training, teaching, counseling, coaxing and coaching. Sixty participants from academia and industry assessed progress made to date and speculated on new tools for building second generation systems.

The Second International Workshop on User Modeling was held March 30- April 1, 1990 in Honolulu, Hawaii. The general chairperson was Dr. Wolfgang Wahlster of the University of Saarbrucken; the program and local arrangements chairperson was Dr. David Chin of the University of Hawaii at Manoa. The workshop was sponsored by AAAI and the University of Hawaii, with AAAI providing eight travel stipends for students.