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
these 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)
[http://www.learningTheory.org/colt2000/]
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: Final 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
UAI-2000 requires electronic submission of papers and abstracts. Papers should
be submitted through the UAI-2000 Conference Management page supported
by Microsoft Research. It can be found at:
http://msrconf.microsoft.com/UAI/CallForPapers.asp
If authors have special circumstances that prevent electronic submission,
arrangements can be made directly with the program chairs below. Papers are due
by February 17, 2000 (11:59PM PST). Electronic abstracts are due before final
papers, by February 11, 2000 (11:59PM PST). Please be sure to submit abstracts
on time.
Important Deadlines:
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 (11:59PM PST)
O Electronic Submission of Full Papers: Thursday, February 17, 2000
(11:59PM PST)
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
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. We are currently negotiating with the publishers
the possible production of a CD-ROM with the proceedings of both UAI-2000 and
COLT-2000.
An outstanding student paper will be selected for special distinction at
UAI-2000. Please see the Instructions for Certifying Student Status at
the UAI-2000 Web page.
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. Please see the Instructions for Preparing Camera-Ready
Copy at
http://www.cs.toronto.edu/uai2000/FormatInstructions.html
for format information and access to style files. The format is identical to
that used for recent UAI conferences; see
http://www2.sis.pitt.edu/~dsl/UAI/uai.html
Conference Organization
Please direct general inquiries to the General Conference Chair at
[EMAIL PROTECTED] Inquiries about the conference program and submission
requirements should be directed to the Program Co-Chairs at
[EMAIL PROTECTED]
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: [EMAIL PROTECTED]
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: [EMAIL PROTECTED]
Moises Goldszmidt
Peakstone Corporation
155A Moffett Park Drive
Sunnyvale, CA 94089
USA
---
Phone: +1 (408) 752-1024
Fax: +1 (408) 752-1040
E-mail: [EMAIL PROTECTED]
Program Committee Area Chairs
Didier Dubois, IRIT
Bruce D'Ambrosio, Oregon State University
Nir Friedman, Hebrew University
Danny Geiger, Technion
Peter Haddawy, University of Wisconsin, Milwaukee
David Heckerman, Microsoft
Eric Horvitz, Microsoft
Finn Jensen, Aalborg University
Daphne Koller, Stanford University
Ramon Lopez de Mantaras, IIIA
David Poole, University of British Columbia
Ross Shachter, Stanford University
Prakash Shenoy, University of Kansas
Michael Wellman, University of Michigan
Program Committee
John Mark Agosta Russell Almond Fahiem Bacchus
Salem Benferhat Philippe Besnard Concha Bielza
Jim Blythe Ronen Brafman Jack Breese
Piero Bonissone Wray Buntine Urszula Chajewska
Max Chickering Greg Cooper Adnan Darwiche
Javier Diez Marek Druzdzel Kazuo Ezawa
Bob Fung Hector Geffner Robert Goldman
Lluis Godo Russ Greiner Joseph Halpern
Othar Hansson Milos Hauskrecht Tommy Jaakola
Frank Jensen Mike Jordan Leslie Kaelbling
Mike Kearns Uffe Kjaerulff Rudolf Kruse
Henry Kyburg Jerome Lang Michael Littman
Anders Madsen Chris Meek Serafin Moral
Eric Neufeld Andrew Ng Ann Nicholson
Kristian Olesen Ron Parr Simon Parsons
Gabriella Pasi David Pennock Mark Peot
Avi Pfeffer Kim Leung Poh Henri Prade
Thomas Richardson Alessandro Saffiotti Bart Selman
Solomon Eyal Shimony Yoram Singer Satinder Singh
Philippe Smets Peter Spirtes Milan Studeny
Jaap Suermondt Moshe Tennenholtz Bo Thiesson
Enric Trillas Linda van der Gaag Michael Wong
Nevin Zhang
