********************************************************************** NEWSLETTER ON DECISION AND REASONING UNDER UNCERTAINTY Issue 99004 Editors: Salem Benferhat, Henri Prade 15.12.1999 Back issues available at http://www.ida.liu.se/ext/etai/dru/index.html ********************************************************************** To subscribe or to correct an entry from the directory of researchers located at: http://cafe.newcastle.edu.au/salem/chercheur.html please send an email to benferhat@irit.fr or prade@irit.fr This newsletter contains: 1. Call for papers : Uncertainty frameworks in nonmonotonic reasoning (NMR) 2. Call for papers : partial knowledge and uncertainty: independence, conditioning, inference 3. Preliminary Call for Papers : UAI-2000 4. New books 4.1. Probabilistic Networks and Expert Systems R.G. Cowell, A.P. Dawid, S.L. Lauritzen, D.J. Spiegelhalter 4.2. Handbook of Fuzzy Sets, 7 volumes, Dubois D., Prade H., (Series Editors), Kluwer, 1998-1999. -------------------------------------------------------------------------------- 1 UNCERTAINTY FRAMEWORKS IN NMR NMR 2000 Special Session April 9-11, Breckenridge, Colorado (Collocated with KR'2000, April 12-15) http://www.cs.engr.uky.edu/nmr2000/uncertainty.html Organizers: Salem Benferhat Universite Paul Sabatier, Toulouse, France (benferha@irit.fr) Henri Prade Universite Paul Sabatier, Toulouse, France (Henri.Prade@irit.fr) Many approaches have been developed for reasoning under incomplete information with uncertain rules having exceptions. Some of them are symbolic and based on a logical framework or on logic programming; others are more numerically oriented and make use of probabilities, qualitative or quantitative possibilities, or of mathematically more general uncertainty frameworks such as belief and plausibility functions, or upper and lower probabilities. The workshop will especially welcome papers contributing to a cross-fertilization of ideas or tools coming from symbolic methods (normative frameworks, bilattices,...) and from numerical approaches (independence, graphical representation, conditioning,...) for NMR and revision purposes. Papers addressing problems related to the practical use and applications of probabilistic, possibilistic and other uncertainty frameworks in NMR are also expected, as well as NMR issues in reasoning about goals and preferences, or about obligations and permissions. Informal proceedings containing accepted papers and other workshop materials will be distributed at the meeting. In addition, they will be published on the web. The general procedure for submission of the special session is identical to the procedure of NMR2000. Format requirements are: 12 double-spaced pages excluding title page and bibliograpy on-line submissions are encouraged (postscript file) IMPORTANT DATES: Submission of papers: January 15, 2000 Acceptance decision by: February 15, 2000 Camera ready copy due: March 8, 2000 Electronic copies of the papers can be submitted to any of the organisers of the session: Salem Benferhat (benferha@irit.fr) Henri Prade (Henri.Prade@irit.fr) A copy also needs to be sent to Mirek Truszczynski (mirek@cs.uky.edu) -------------------------------------------------------------------------------- 2 PARTIAL KNOWLEDGE AND UNCERTAINTY: INDEPENDENCE, CONDITIONING, INFERENCE ROME, Italy May 4-6, 2000 AIMS and SCOPE of the Meeting: To give an overview of the state-of-the-art and of research trends concerning the various aspects and methodologies for the treatment of partial knowledge and uncertainty, with a particular emphasis on independence (stochastic and logical), conditioning, and inference STRUCTURE: Invited lectures, contributed papers (oral and poster sessions) that should also discuss (in their mathematical framework) a significant case-study VENUE: The meeting will take place (from Thursday afternoon to Saturday) at Aula del Chiostro in Via Eudossiana 18, Rome, the main seat of the Engineering Faculty of University "La Sapienza", which is located in a magnificent spot in the central and archeological part of Rome: the Colosseum, the church of "S.Pietro in Vincoli" (with the famous Moses by Michelangelo) and the Domus Aurea are among the monuments that are in the immediate neighbourhood, at a walking distance of less than five minutes SUBMISSION OF PAPERS: An extended abstract of 2-4 pages (A4) must be sent (preferably in electronic form - file Latex by email - or else as a camera-ready paper) to Prof. Romano Scozzafava, Dipartimento Metodi e Modelli Matematici, Via Scarpa 16, 00161 Roma, Italy Email: romscozz@dmmm.uniroma1.it Deadline: March 31, 2000 PROCEEDINGS: A selection of refereed papers might be published on an international journal (to be specified later) FOR DETAILS, REGISTRATION AND ACCOMODATION FORMS, VISIT THE WEB SITE http://www.dmmm.uniroma1.it/~uncertainty2000 -------------------------------------------------------------------------------- 3. UAI-2000: The Sixteenth Conference on Uncertainty in Artificial Intelligence Stanford University, Stanford, CA June 30 - July 3, 2000 Please check the UAI-2000 home page [http://www.cs.toronto.edu/uai2000] regularly for updates on conference details, submission requirements, etc. 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 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. 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 Peakstone 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 -------------------------------------------------------------------------------- 4. New books -------------------------------------------------------------------------------- 4.1. Probabilistic Networks and Expert Systems R.G. Cowell, A.P. Dawid, S.L. Lauritzen, D.J. Spiegelhalter (Statistics for Engineering and Information Science. Eds.: M. Jordan, S.L. Lauritzen, J. Lawless, V. Nair. formerly Statistics for Engineering and Physical Science) Probabilistic expert systems are graphical networks which support the modelling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors over a number of years, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms, emphasizing those cases in which exact answers are obtainable. It covers both the updating of probabilistic uncertainty in the light of new evidence and statistical inference, about unknown probabilities or unknown model structure, in the light of new data. The book will be of interest to researchers and graduate students in artificial intelligence who desire an under- standing of the mathematical and statistical basis of probabilistic expert systems, and to students and research workers in statistics wanting an introduction to this fascinating and rapidly developing field. The careful attention to detail will also make this work an important reference source for all those involved in the theory and applications of probabilistic expert systems. Contents: Introduction.- Logic, Uncertainty, and Probability.- Building and Using Probabilistic Networks.- Graph Theory.- Markov Properties on Graphs.- Discrete Networks.- Gaussian and Mixed Discrete-Gaussian Networks.- Discrete Multistage Decision Networks.- Learning About Probabilities.- Checking Models Against Data.- 1999. 333 pp. 45 illus. Hardcover $69.95 ISBN 0-387-98767-3 Structural Learning. Statistics, Computer Science 4.2. Handbook of Fuzzy Sets, 7 volumes, Dubois D., Prade H., (Series Editors), Kluwer, 1998-1999. 1. Dubois D., Prade H., (Eds.) Fundamentals of Fuzzy Sets. The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999. 2. Hoehle U. and Rodabaugh S., Eds. Mathematics of Fuzzy Sets: Logic, Topology and Measure Theory. The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999. 3. Bezdek J., Dubois D., Prade H., (Eds). Fuzzy Sets in Approximate Reasoning and Information Systems. The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999. 4. Bezdek J., Keller J., Krishnapuram R., and Pal N. R. Fuzzy Models and Algorithms for Pattern Recognition and Image Processing, The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999. 5. Slowinski R., Ed. Fuzzy Sets in Decision Analysis, Operations Research and Statistics, The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1998 6. Nguyen H.T. and Sugeno M. (Eds.) Fuzzy Systems: Modeling and Control. The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1998. 7. Zimmermann H.-J. (Ed.) Practical Applications of Fuzzy Technologies. The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999.