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

John Deere (Moline, Ill.), a manufacturer of agricultural and industrial equipment, has adopted a genetic algorithm-based solution to solve its factory scheduling problems. John Deere is using genetic algorithms to streamline scheduling at its factories, Sarasota County Detention Center knowledge in a system model and balancing an increasing number of (Sarasota, Fla.) has incorporated The center will use the The Royal Sonesta Hotel Boston Martin Marietta Magnesia Specialties new system to identify and confirm (Cambridge, Mass.) has deployed a (Woodville, Ohio), a producer of identities of inmates prior to being speech-driven automated attendant magnesia chemicals for industrial released from the facility. LucasArts Entertainment (San technology to automatically answer Primary objectives for the system Rafael, Calif.) has deployed a casebased and direct telephone calls, enabling are to increase production yet maintain reasoning self-service customer each caller direct access to a registered quality and decrease energy costs. This Report (Cuyahoga Falls, Ohio; Shanghai PuDong International Airport resource-allocation application evaluates www.lionhrtpub.com), The react to unforeseen events in real time.

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 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.

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.

Many different architectures have been proposed for the design of autonomous agents. In this article, the application of the belief-desire-intention architecture to the artificial soccer domain is described. We show how it supports efficient deliberation in a highly dynamic environment.

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.

Modeling various aspects of language-syntax, semantics, pragmatics, and discourse, among others -- by the use of constrained formal-computational systems, just adequate for such modeling, has proved to be an effective research strategy, leading to deep understanding of these aspects, with implications for both machine processing and human processing. This approach enables one to distinguish between the universal and stipulative constraints. This is in contrast to an approach where we start with the most powerful formal-computational system and then model the phenomena by making all constraints stipulative in a sense. The use of constrained systems for modeling leads to some novel ways of describing locality of structures and brings out the relationship between the complexity of description of primitives and local computations over them. These ideas serve to unify theoretical, computational, and statistical aspects of natural language processing in AI. It is expected that this approach will also be productive in other domains of AI.

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.

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.