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S E C O N D C A L L F O R P A P E R S
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** U A I 96 **
THE TWELFTH ANNUAL CONFERENCE ON
UNCERTAINTY IN ARTIFICIAL INTELLIGENCE
August 1-3, 1996
Reed College
Portland, Oregon, USA
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See the UAI-96 WWW page at http://cuai-96.microsoft.com/
CALL FOR PAPERS
The effective handling of uncertainty is critical in designing,
understanding, and evaluating computational systems tasked with making
intelligent decisions. For over a decade, the Conference on
Uncertainty in Artificial Intelligence (UAI) has served as the central
meeting on advances in methods for reasoning under uncertainty in
computer-based systems. The conference is the annual international
forum for exchanging results on the use of principled
uncertain-reasoning methods to solve difficult challenges in
AI. Theoretical and empirical contributions first presented at UAI
have continued to have significant influence on the direction and
focus of the larger community of AI researchers.
The scope of UAI covers a broad spectrum of approaches to automated
reasoning and decision making under uncertainty. Contributions to the
proceedings address topics that advance theoretical principles or
provide insights through empirical study of applications. Interests
include quantitative and qualitative approaches, and traditional as
well as alternative paradigms of uncertain reasoning. Innovative
applications of automated uncertain reasoning have spanned a broad
spectrum of tasks and domains, including systems that make autonomous
decisions and those designed to support human decision making through
interactive use.
We encourage submissions of papers for UAI-96 that report on advances
in the core areas of representation, inference, learning, and
knowledge acquisition, as well as on insights derived from building or
using applications of uncertain reasoning.
Topics of interest include (but are not limited to):
>> Foundations
* Theoretical foundations of uncertain belief and decision
* Uncertainty and models of causality
* Representation of uncertainty and preference
* Generalization of semantics of belief
* Conceptual relationships among alternative calculi
* Models of confidence in model structure and belief
>> Principles and Methods
* Planning under uncertainty
* Temporal reasoning
* Markov processes and decisions under uncertainty
* Qualitative methods and models
* Automated construction of decision models
* Abstraction in representation and inference
* Representing intervention and persistence
* Uncertainty and methods for learning and datamining
* Computation and action under limited resources
* Control of computational processes under uncertainty
* Time-dependent utility and time-critical decisions
* Uncertainty and economic models of problem solving
* Integration of logical and probabilistic inference
* Statistical methods for automated uncertain reasoning
* Synthesis of Bayesian and neural net techniques
* Algorithms for uncertain reasoning
* Advances in diagnosis, troubleshooting, and test selection
>> Empirical Study and Applications
* Empirical validation of methods for planning, learning, and diagnosis
* Enhancing the human--computer interface with uncertain reasoning
* Uncertain reasoning in embedded, situated systems (e.g., softbots)
* Automated explanation of results of uncertain reasoning
* Nature and performance of architectures for real-time reasoning
* Experimental studies of inference strategies
* Experience with knowledge-acquisition methods
* Comparison of repres. and inferential adequacy of different calculi
* Uncertain reasoning and information retrieval
For papers focused on applications in specific domains, we suggest
that the following issues be addressed in the submission:
- Why was it necessary to represent uncertainty in your domain?
- What are the distinguishing properties of the domain and problem?
- What kind of uncertainties does your application address?
- Why did you decide to use your particular uncertainty formalism?
- What theoretical problems, if any, did you encounter?
- What practical problems did you encounter?
- Did users/clients of your system find the results useful?
- Did your system lead to improvements in decision making?
- What approaches were effective (ineffective) in your domain?
- What methods were used to validate the effectiveness of the systems?
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SUBMISSION AND REVIEW OF PAPERS
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Papers submitted for review should represent original, previously
unpublished work (details on policy on submission uniqueness are
available at the UAI 96 www homepage). Submitted papers will be
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 Twelfth Conference on
Uncertainty in Artificial Intelligence, published by Morgan Kaufmann
Publishers. Outstanding student papers will be selected for special
distinction.
Submitted papers must be at most 20 pages of 12pt Latex article style
or equivalent (about 4500 words).
We strongly encourage the electronic submission of papers. To submit
a paper electronically, send an email message to
uai@microsoft.com
that includes the following information (in this order):
* Paper title (plain text)
* Author names, including student status (plain text)
* Surface mail and email address for a contact author (plain text)
* A short abstract including keywords or topic indicators (plain text)
An electronic version of the paper (Postscript format) should be
submitted simultaneously via ftp to: cuai-96.microsoft.com/incoming.
Files should be named $.ps, where $ is an identifier created from the
first five letters of the last name of the first author, followed by
the first initial of the author's first name. Multiple submissions by
the same first author should be indicated by adding a number (e.g.,
pearlj2.ps) to the end of the identifier. Authors will receive
electronic confirmation of the successful receipt of their articles.
Authors unable to access ftp should electronically mail the first four
items
and the Postscript file of their paper to uai@microsoft.com. Authors
unable to submit Postscript versions of their paper should send the
first four items in email and 5 copies of the complete paper to one of
the Program Chairs at the addresses listed below.
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Important Dates (Note revisions)
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>> Submissions must be received by 5PM local time: March 1, 1996
>> Notification of acceptance on or before: April 19, 1996
>> Camera-ready copy due: May 15, 1996
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Program Cochairs:
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Eric Horvitz
Decision Theory Group
Microsoft Research, 9S
Redmond, WA 98052
Phone: (206) 936 2127
Fax: (206) 936 0502
Email: horvitz@microsoft.com
WWW: http://www.research.microsoft.com/research/dtg/horvitz/
Finn Jensen
Department of Mathematics and Computer Science
Aalborg University
Fredrik Bajers Vej 7,E
DK-9220 Aalborg OE
Denmark
Phone: +45 98 15 85 22 (ext. 5024)
Fax: +45 98 15 81 29
Email: fvj@iesd.auc.dk
WWW: http://www.iesd.auc.dk/cgi-bin/photofinger?fvj
General Conference Chair (General conference inquiries):
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Steve Hanks
Department of Computer Science and Engineering, FR-35
University of Washington
Seattle, WA 98195
Tel: (206) 543 4784
Fax: (206) 543 2969
Email: hanks@cs.washington.edu
Program Committee
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Fahiem Bacchus (U Waterloo) * Salem Benferhat (U Paul Sabatier) * Mark
Boddy (Honeywell) * Piero Bonissone (GE) * Craig Boutilier (U Brit
Columbia) * Jack Breese (Microsoft) * Wray Buntine (Thinkbank) * Luis
M. de Campos * (U Granada) * Enrique Castillo (U Cantabria) * Eugene
Charniak (Brown) * Greg Cooper (U Pittsburgh) * Bruce D'Ambrosio
(Oregon State) * Paul Dagum (Stanford) * Adnan Darwiche (Rockwell) *
Tom Dean (Brown) * Denise Draper (Rockwell) * Marek Druzdzel (U
Pittsburgh) * Didier Dubois (Paul Sabatier) * Ward Edwards (USC) *
Kazuo Ezawa (ATT Labs) * Nir Friedman (Stanford) * Robert Fung
(Prevision) * Linda van der Gaag (Utrecht U) * Hector Geffner (Simon
Bolivar) * Dan Geiger (Technion) * Lluis Godo (Barcelona) * Robert
Goldman (Honeywell) * Moises Goldszmidt (Rockwell) * Adam Grove (NEC)
* Peter Haddawy (U Wisc-Milwaukee) * Petr Hajek (Czech Acad Sci) *
Joseph Halpern (IBM) * Steve Hanks (U Wash) * Othar Hansson (Berkeley)
* Peter Hart (Ricoh) * David Heckerman (Microsoft) * Max Henrion
(Lumina) * Frank Jensen (Hugin) * Michael Jordan (MIT) * Leslie Pack
Kaelbling (Brown) * Keiji Kanazawa (Microsoft) * Uffe Kjaerulff (U
Aalborg) * Daphne Koller (Stanford) * Paul Krause (Imp. Cancer Rsch
Fund) * Rudolf Kruse (U Braunschweig) * Henry Kyburg (U Rochester) *
Jerome Lang (U Paul Sabatier) * Kathryn Laskey (George Mason) * Paul
Lehner (George Mason) * John Lemmer (Rome Lab) * Tod Levitt (IET) *
Ramon Lopez de Mantaras (Spanish Sci. Rsch Council) * David Madigan (U
Wash) * Eric Neufeld (U Saskatchewan) * Ann Nicholson (Monash U) *
Judea Pearl (UCLA) * Mark Peot (Stanford) * Kim Leng Poh, (Natl U
Singapore) * David Poole (U Brit Columbia) * Henri Prade (U Paul
Sabatier) * Greg Provan (Inst. Learning Sys) * Enrique Ruspini (SRI) *
Romano Scozzafava (Dip. Mo. Met., Rome) * Ross Shachter (Stanford) *
Prakash Shenoy (U Kansas) * Philippe Smets (U Bruxelles) * David
Spiegelhalter (Cambridge U) * Peter Spirtes (CMU) * Milan Studeny
(Czech Acad Sci) * Sampath Srinivas (Microsoft) * Jaap Suermondt (HP
Labs) * Marco Valtorta (U S.Carolina) * Michael Wellman (U Michigan) *
Nic Wilson (Oxford Brookes U) * Y. Xiang (U Regina) * Hong Xu (U
Bruxelles) * John Yen (Texas A&M) * Lian Wen Zhang, (Hong Kong U) *
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UAI-96 will occur right before KDD-96, AAAI-96, and the AAAI workshops,
and will be in close proximity to these meetings.
* * *
UAI 96 will include a full-day tutorial program on uncertain reasoning
on the day before the main UAI 96 conference (Wednesday, July 31) at
Reed College. Details on the tutorials are available on the UAI 96
www homepage.
* * *
Refer to the UAI-96 WWW home page for late-breaking information:
http://cuai-96.microsoft.com/