UAI-2000: The Sixteenth Conference on Uncertainty in Artificial Intelligence Stanford University, Stanford, CA June 30 - July 3, 2000 As we approach the new millenium, advances in the theory and practice of artificial intelligence have pushed intelligent systems to the forefront of the information technology sector. At the same time, uncertainty managament has come to play a central role in the development of intelligent systems. The Conference on Uncertainty in Artificial intelligence, organized annually under the auspices of the Association for Uncertainty in AI (AUAI) [http://www.auai.org], is the premier international forum for exchanging results on the use of principled uncertain-reasoning methods in intelligent systems. The Sixteenth Conference on Uncertainty in Artificial, UAI-2000, will be held from June 30 - July 3, 2000, at Stanford University. The main technical program will be run from July 1-3, with UAI's regular tutorial program and several workshops to be held on June 30. As in 1998 in Madison, WI, this year the conference will be co-located with the International Conference on Machine Learning and the Conference on Compuational Learning theory. * The Seventeenth International Conference on Machine Learning (ICML-2000) [http://hypatia.stanford.edu/icml2k] * Conference on Computational Learning Theory (COLT-2000) Registrants to any of COLT, ICML, or UAI will be allowed to attend, without additional cost, the technical sessions of the other two conferences. Please check the UAI-2000 home page [http://www.cs.toronto.edu/~uai2000] regularly for updates on conference details, submission requirements, etc. =================== UAI-2000: Preliminary Call for Papers Uncertainty management is a key enabling technology for the development of intelligent systems. Since 1985, the Conference on Uncertainty in Artificial Intelligence (UAI) has been the primary international forum for exchanging results on the use of principled uncertain-reasoning methods in intelligent systems. The conference has catalyzed advances in fundamental theory, efficient algorithms, and practical applications. Theory and technology first presented at UAI have been proven by their wide application in the scientific, commercial, and industrial communities, and by the success of the systems in which these technologies have been employed. The UAI Proceedings have become a fundamental reference for researchers and practitioners who want to know about both theoretical advances and the latest applied developments in the field. The scope of UAI is wide, covering a broad spectrum of approaches to automated reasoning, learning, decision making and knowledge acquisition under uncertainty. Contributions range from those that that advance theoretical principles to those that provide insights through the empirical study of applications, from quantitative to qualitative approaches, from traditional to non-classical paradigms for uncertain reasoning, and from autonomous systems to those designed to support human decision making. We encourage submissions of papers for UAI-2000 that report on advances in the core areas of representation, inference, learning, decision making, and knowledge acquisition, as well those dealing with on insights derived from the construction and use of applications involving uncertain reasoning. Topics of interest include (but are not limited to): O Foundations * Relationships between different uncertainty calculi * Higher-order uncertainty and model confidence * Representation of uncertainty and preferences * Revision of belief, combination of information from multiple sources * Semantics of belief * Theoretical foundations of uncertainty and decision-making * Uncertainty and models of causality O Principles and Methods * Algorithms for reasoning and decision making under uncertainty * Automated construction of inference and decision models * Combination of models from different sources * Control of computational processes under uncertainty * Data structures for representation and inference * Decision making under uncertainty * Diagnosis, troubleshooting, and test selection * Enhancing human-computer interaction with uncertain reasoning * Explanation of results of uncertain reasoning * Formal languages to represent uncertain information * Hybridization of methodologies and techniques * Integration of logic with uncertainty calculi * Markov decision processes * Methods based on probability, possibilistic and fuzzy logic, belief functions, rough sets, and other formalisms * Multi-agent reasoning and Economic Models involving uncertainty * Planning under uncertainty * Qualitative methods and models * Reasoning at different levels of abstraction * Reinforcement Learning * Representation and Discovery of causal relationships * Resource-bounded Computation (inference, learning, decision making) * Statistical Methods for Automated Uncertain Reasoning * Temporal reasoning * Time-critical decisions * Uncertain reasoning and information retrieval * Uncertainty and methods for learning and data mining O Empirical Studies and Applications * Comparison of representation and inferential adequacy of different calculi * Empirical validation of methods for planning, learning, and diagnosis * Experience with knowledge-acquisition methods * Experimental studies of inference strategies * Methodologies for problem modeling * Nature and performance of architectures for real-time reasoning * Uncertain reasoning in embedded, situated systems For papers focused on applications in specific domains, we suggest that the following issues be addressed in the submission: O Why was it necessary to represent uncertainty in your domain? O What are the distinguishing properties of the domain and problem? O Why did you decide to use your particular uncertainty formalism? O Which practical procedure did you follow to build the application? O What theoretical problems, if any, did you encounter? O What practical problems did you encounter? O Did users/clients of your system find the results useful? O Did your system lead to improvements in decision quality? O What approaches were effective (ineffective) in your domain? O What methods were used to validate the effectiveness of the system? Submission Information Precise submission details will be made available in the final call for papers. However, UAI will require electronic submission of papers and abstracts (if authors have special circumstances that prevent electronic submission, arrangements can be made directly with the program chairs below). Papers will be due (tentatively) on February 17, 2000. The Final Call for Papers will be made available in the near future at the UAI-2000 Home Page [http://www.cs.toronto.edu/~uai2000]. Please check that page regularly for up-to-date information on the conference. Preliminary Deadlines (to be confirmed in the final CFP): The deadline for electronic submissions to UAI-2000 is Thursday, February 17, 2000. Other important dates: O Electronic Submission of Abstracts (200 Word Limit): Friday, February 11, 2000 O Electronic Submission of Full Papers: Thursday, February 17, 2000 O Author Notification of Accepted Papers: Sunday, April 9, 2000 O Camera-ready Copy of Accepted Papers due: Tuesday, May 9, 2000 O Workshops and Tutorials: Friday, June 30, 1999 O Technical Program: Saturday, July 1 - Monday, July 3 Submission Requirements (to be confirmed in the final CFP): Papers submitted for review should represent original, previously unpublished work. Papers should not be under review for presentation in any other conference; however, an extended version of the paper may be under review for publication in a scientific journal. Submitted papers will be carefully evaluated on the basis of originality, significance, technical soundness, and clarity of exposition. Papers may be accepted for presentation in plenary or poster sessions. All accepted papers will be included in the Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, published by Morgan Kaufmann Publishers. An outstanding student paper will be selected for special distinction at UAI-2000. Instructions to be considered for this award will be provided in the final Call for Papers. Authors are strongly encouraged to submit papers in the proceedings format. Submitted papers must be no more than eight pages in proceedings format, including figures and bibliography (about 5600 words). Accepted papers will be alloted eight pages in the conference proceedings, with two additional pages available for a fee. Format information and links to appropriate style files for paper preparation will be made available with the Final Call for Papers. The format will be identical to that used for recent UAI conferences; see Uncertainty in Artificial Intelligence Conferences: Electronic Proceedings [http://www2.sis.pitt.edu/~dsl/UAI/uai.html] Conference Organization Please direct general inquiries to the General Conference Chair at klaskey@gmu.edu. Inquiries about the conference program and submission requirements should be directed to the Program Co-Chairs at uai00-pchairs@cs.toronto.edu. Conference Chairs General Conference Chair: Kathryn Blackmond Laskey Department of Systems Engineering and Operations Research George Mason University Fairfax, VA 22030-4444 USA --- Phone: +1 (703) 993-1644 Fax: +1 (703) 993-1521 E-mail: klaskey@gmu.edu Program Co-chairs: Craig Boutilier Department of Computer Science University of Toronto Toronto, ON M5S 3H5 CANADA --- Phone: +1 (416) 946-5714 Fax: +1 (416) 978-1455 E-mail: cebly@cs.toronto.edu Moises Goldszmidt Peasktone Corporation 155A Moffett Park Drive Sunnyvale, CA 94089 USA --- Phone: +1 (408) 752-1024 Fax: +1 (408) 752-1040 E-mail: moises@cs.stanford.edu