************************************************************************** NEWSLETTER ON DECISION AND REASONING UNDER UNCERTAINTY Issue 98002 Editors: Salem Benferhat, Henri Prade 3.8.1998 Back issues available at http://www.ida.liu.se/ext/etai/dru/binf.html ************************************************************************** This first newsletter after the introductory one contains: 1. Abstract of a submitted paper by David Poole 2. Technical program of UAI-98 3. Call for papers of Ecsqaru-99 4. Call for papers of Uncertainty-99 5. Table of contents of IPMU-98 proceedings ========================================================================== 1. Abstract of a submited paper by David Poole ========================================================================== Title: Decision Theory, the Situation Calculus and Conditional Plans. Authors: David Poole Abstract: This paper shows how to combine decision theory and logical representations of actions in a manner that seems natural for both. In particular, we assume an axiomatization of the domain in terms of situation calculus, using what is essentially Reiter's solution to the frame problem, in terms of the completion of the axioms defining the state change. Uncertainty is handled in terms of the independent choice logic, which allows for independent choices and a logic program that gives the consequences of the choices. As part of the consequences are a specification of the utility of (final) states, and how (possibly noisy) sensors depend on the state. The robot adopts conditional plans, similar to the GOLOG programming language. Within this logic, we can define the expected utility of a conditional plan, based on the axiomatization of the actions, the sensors and the utility. Sensors can be noisy and actions can be stochastic. The planning problem is to find the plan with the highest expected utility. This representation is related to recent structured representations for partially observable Markov decision processes (POMDPs); here we use stochastic situation calculus rules to specify the state transition function and the reward/value function. Finally we show that with stochastic frame axioms, action representations in probabilistic STRIPS are exponentially larger than using the representation proposed here. Poscript file: http://www.ep.liu.se/ea/cis/1998/008/cis98008.ps ========================================================================== 2. Technical program of UAI-98 ========================================================================== Fourteenth Conference on Uncertainty in Artificial Intelligence July 24-26, 1998 University of Wisconsin Business School Madison, Wisconsin, USA UAI'98 Conference Program Joint COLT/ICML/UAI Reception Conference and Course Registration Thursday, July 23, 6:00-10:00 pm Grainger Hall (Elwell Commons/Courtyard) Friday, July 24, 1998 Conference and Course Registration 7:30-8:15 AM First Floor Atrium, Grainger Hall Welcome to Madison and Opening Remarks of the Collocated Conferences 8:15-8:30 AM Jude Shavlik Mills Concert Hall, Humanities Building Joint COLT/ICML/UAI Invited Talk I 8:30-9:30 AM Reinforcement Learning: How Far Can It Go? Richard Sutton Introduction by Leslie Pack Kaelbling Mills Concert Hall, Humanities Building Break 9:30-10:00 AM First Floor Atrium, Grainger Hall UAI Plenary Session I 10:00-11:40 AM Session Chair: Kathryn B. Laskey Room 1100 Grainger Hall (Morgridge Auditorium) Utility Elicitation as a Classification Problem Urszula Chajewska, Lise Getoor, Joseph Norman, and Yuval Shahar Best Student Paper Award Learning from What You Don't Observe Mark A. Peot and Ross D. Shachter Switching Portfolios Yoram Singer The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users Eric Horvitz, Jack Breese, David Heckerman, David Hovel, and Koos Rommelse Lunch 11:40 AM -1:30 PM First Floor Atrium, Grainger Hall Friday lunch ticket and UAI-98 Conference badge required please. UAI Plenary Session II 1:30-3:10 PM Session Chair: Peter Spirtes Room 1100 Grainger Hall (Morgridge Auditorium) On the Geometry of Bayesian Graphical Models with Hidden Variables Raffaella Settimi and Jim Q. Smith Graphical Models and Exponential Families Dan Geiger and Christopher Meek Bayesian Networks from the Point of View of Chain Graphs Milan Studeny Psychological and Normative Theories of Causal Power and the Probabilities of Causes Clark Glymour Break 3:10-3:30 PM First -Floor Atrium, Grainger Hall UAI Poster Session: Overview of Presentations 3:30-4:05 PM Session Chair: Ross D. Shachter Room 1100 Grainger Hall (Morgridge Auditorium) UAI Poster Session 4:05-6:30 PM Room 5120 AB (Capitol Conference), Grainger Hall A Hybrid Algorithm to Compute Marginal and Joint Beliefs in Bayesian Networks and Its Complexity Mark Bloemeke and Marco Valtorta Marginalizing in Undirected Graph and Hypergraph Models Enrique F. Castillo, Juan Ferrándiz, and Pilar Sanmartín Dealing with Uncertainty in Situation Assessment: Towards a Symbolic Approach Charles Castel, Corine Cossart, and Catherine Tessier Dynamic Jointrees Adnan Darwiche On the Semi-Markov Equivalence of Causal Models Benoit Desjardins Comparative Uncertainty, Belief Functions and Accepted Beliefs Didier Dubois, Hélène Fargier, and Henri Prade Inferring Informational Goals from Free-Text Queries: A Bayesian Approach David Heckerman and Eric Horvitz Any Time Probabilistic Reasoning for Sensor Validation Pablo H. Ibargüengoytia, L. Enrique Sucar, and Sunil Vadera Measure Selection: Notions of Rationality and Representation Independence Manfred Jaeger Dealing with Uncertainty on the Initial State of a Petri Net Iman Jarkass and Michèle Rombaut A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions Vasilica Lepar and Prakash P. Shenoy Using Qualitative Relationships for Bounding Probability Distributions Chao-Lin Liu and Michael P. Wellman Magic Inference Rules for Probabilistic Deduction under Taxonomic Knowledge Thomas Lukasiewicz Lazy Propagation in Junction Trees Anders L. Madsen and Finn V. Jensen Constructing Situation Specific Belief Networks Suzanne M. Mahoney and Kathryn Blackmond Laskey Resolving Conflicting Arguments under Uncertainties Benson Hin-Kwong Ng, Kam-Fai Wong, and Boon-Toh Low Logarithmic Time Parallel Bayesian Inference David M. Pennock Context-Specific Approximation in Probabilistic Inference David Poole Planning with Partially Observable Markov Decision Processes: Advances in Exact Solution Method Nevin L. Zhang and Stephen S. Lee Joint Reception, Banquet, and Invited Talk 7:00-9:30 PM Madison Convention Center Banquet Talk: 2.5 Millennia of Directed Graphs David Spiegelhalter Introduction by Steffen Lauritzen ---------------------------------------------------------------------------- Saturday, July 25, 1998 Conference and Course Registration 8:00-8:30 AM First Floor Atrium, Grainger Hall Joint COLT/ICML/UAI Invited Talk II 8:30-9:30 AM Learning Agents for Uncertain Environments Stuart Russell Introduction by Yishay Mansour Mills Concert Hall, Humanities Building Break 9:30-10:00 AM First Floor Atrium, Grainger Hall UAI Plenary Session III 10:00-11:40 AM Session Chair: Fahiem Bacchus Room 1100 Grainger Hall (Morgridge Auditorium) Tractable Inference for Complex Stochastic Processes Xavier Boyen and Daphne Koller Structured Reachability Analysis for Markov Decision Processes Craig Boutilier, Ronen I. Brafman, and Christopher Geib Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems Ronald Parr Hierarchical Solution of Markov Decision Processes Using Macro-actions Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling, Thomas Dean, and Craig Boutilier Lunch 11:40 AM-1:15 PM Rooms 3275 (Executive Dining Room) and 3180, Grainger Hall Saturday lunch ticket and UAI-98 Conference badge required please. UAI Invited Talk 1:15-2:15 PM Treatment Choice in Heterogeneous Populations Using Experiments without Covariate Data Charles F. Manski Introduction by Greg Cooper Room 1100 Grainger Hall (Morgridge Auditorium) UAI Panel Discussion 2:15-3:10 PM Bayesian Network Interchange Format: A Dominated Option? Panel Chairs: Bruce D'Ambrosio and Tod Levitt Room 1100 Grainger Hall (Morgridge Auditorium) Break 3:10-3:30 PM First Floor Atrium, Grainger Hall UAI Plenary Session IV 3:30-4:45 PM Session Chair: Peter Haddawy Room 2120 Grainger Hall (Kellner Auditorium) Updating Sets of Probabilities Adam J. Grove and Joseph Y. Halpern Irrelevance and Independence Relations in Quasi-Bayesian Networks Fabio Cozman Merging Uncertain Knowledge Bases in a Possibilistic Logic Framework Salem Benferhat and Claudio Sossai Joint Poster Session: Overview of UAI Presentations 4:45-5:20 PM Session Chair: Marco Ramoni Room 2120 Grainger Hall (Kellner Auditorium) Joint COLT/ICML/UAI/ILP Poster Session 7:00-8:00 PM Optional staffing of posters 8:00-9:30 PM Those posters staffed for which the first author's last name is in A-L 9:30-11:00 PM Those posters staffed for which the first author's last name is in M-Z 11:00-12:00 MN Optional staffing of posters Madison Convention Center This poster session will include UAI, COLT, ILP and ICML papers. See COLT'98 , ICML'98 , and COLT'98 Conference Schedules for papers from the other conferences. Each paper has a label assigned ([UAI-#] in the case of UAI papers). The posters from all the conferences will be organized in alphanumeric order of their labels. UAI PRESENTATIONS Note: Papers with an asterisk are both presented as plenary papers at UAI and as posters at the joint poster session. [UAI-1] Tractable Inference for Complex Stochastic Processes (*) Xavier Boyen and Daphne Koller [UAI-2] Empirical Analysis of Predictive Algorithms for Collaborative Filtering John S. Breese, David Heckerman, and Carl Kadie [UAI-3] Query Expansion in Information Retrieval Systems using a Bayesian Network-Based Thesaurus Luis M. de Campos, Juan M. Fernández, and Juan F. Huete [UAI-4] Utility Elicitation as a Classification Problem (*) Urszula Chajewska, Lise Getoor, Joseph Norman, and Yuval Shahar [UAI-5] The Bayesian Structural EM Algorithm (*) Nir Friedman [UAI-6] Learning the Structure of Dynamic Probabilistic Networks Nir Friedman, Kevin Murphy, and Stuart Russell [UAI-7] Learning by Transduction Alex Gammerman, Vladimir Vovk, and Vladimir Vapnik [UAI-8] Graphical Models and Exponential Families (*) Dan Geiger and Christopher Meek [UAI-9] Psychological and Normative Theories of Causal Power and the Probabilities of Causes (*) Clark Glymour [UAI-10] Minimum Encoding Approaches for Predictive Modeling Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, and Henry Tirri [UAI-11] Toward Case-Based Preference Elicitation: Similarity Measures on Preference Structures Vu Ha and Peter Haddawy [UAI-12] Solving POMDPs by Searching in Policy Space Eric A. Hansen [UAI-13] Evaluating Las Vegas Algorithms -- Pitfalls and Remedies (*) Holger H. Hoos and Thomas Stützle [UAI-14] An Anytime Algorithm for Decision Making under Uncertainty Michael C. Horsch and David Poole [UAI-15] The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users (*) Eric Horvitz, Jack Breese, David Heckerman, David Hovel, and Koos Rommelse [UAI-16] Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results Wenxin Jiang and Martin A. Tanner [UAI-17] Exact Inference of Hidden Structure from Sample Data in Noisy-OR Networks Michael Kearns and Yishay Mansour [UAI-18] Large Deviation Methods for Approximate Probabilistic Inference Michael Kearns and Lawrence Saul [UAI-19] Mixture Representations for Inference and Learning in Boltzmann Machines Neil D. Lawrence, Christopher M. Bishop, and Michael I. Jordan [UAI-20] An Experimental Comparison of Several Clustering and Initialization Methods Marina Meila and David Heckerman [UAI-21] A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data Stefano Monti and Gregory F. Cooper [UAI-22] Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding Irina Rish, Kalev Kask, and Rina Dechter [UAI-23] Decision Theoretic Foundations of Graphical Model Selection Paola Sebastiani and Marco Ramoni [UAI-24] On the Geometry of Bayesian Graphical Models with Hidden Variables (*) Raffaella Settimi and Jim Q. Smith [UAI-25] Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams) Ross D. Shachter [UAI-26] Switching Portfolios (*) Yoram Singer [UAI-27] Bayesian Networks from the Point of View of Chain Graphs (*) Milan Studeny [UAI-28] Learning Mixtures of DAG Models (*) Bo Thiesson, Christopher Meek, David Maxwell Chickering, and David Heckerman ---------------------------------------------------------------------------- Sunday, July 26, 1998 Conference and Course Registration 8:00-8:30 AM First Floor Atrium, Grainger Hall Joint COLT/ICML/UAI Invited Talk III 8:30-9:30 AM Conditional Independence: A Structural Framework for Uncertainty Philip Dawid Introduction by Prakash P.Shenoy Mills Concert Hall, Humanities Building Break 9:30-10:00 AM First Floor Atrium, Grainger Hall UAI Plenary Session V 10:00-11:40 AM Session Chair: Salem Benferhat Room 1100 Grainger Hall (Morgridge Auditorium) Axiomatizing Causal Reasoning Joseph Y. Halpern Qualitative Decision Theory with Sugeno Integrals Didier Dubois, Henri Prade, and Régis Sabbadin On the Acceptability of Arguments in Preference-Based Argumentation Leila Amgoud and Claudette Cayrol >From Likelihood to Plausibility Paul-André Monney Lunch 11:40 AM-12:45 PM (Note: There is an abbreviated lunch today.) Rooms 3275 (Executive Dining Room) and 3180, Grainger Hall Sunday lunch ticket and UAI-98 conference badge required please. UAI Business Meeting: All are invited 12:45-1:30 PM Room 1100 Grainger Hall (Morgridge Auditorium) UAI Plenary Session VI 1:30-3:10 PM Session Chair: John Mark Agosta Room 1100 Grainger Hall (Morgridge Auditorium) Flexible and Approximate Computation through State-Space Reduction Weixiong Zhang Incremental Tradeoff Resolution in Qualitative Probabilistic Networks Chao-Lin Liu and Michael P. Wellman Probabilistic Inference in Influence Diagrams Nevin L. Zhang Evaluating Las Vegas Algorithms - Pitfalls and Remedies Holger H. Hoos and Thomas Stützle Break 3:10-3:30 PM First Floor Atrium, Grainger Hall UAI Plenary Session VII 3:30-4:20 PM Session Chair: Michael I. Jordan Room 1100 Grainger Hall (Morgridge Auditorium) Learning Mixtures of DAG Models Bo Thiesson, Christopher Meek, David Maxwell Chickering, and David Heckerman The Bayesian Structural EM Algorithm Nir Friedman Joint Panel Discussion 4:30-5:30 PM Current Issues and Open Problems Panel Chairs: Tom Dietterich, David Heckerman, and Michael Kearns Mills Concert Hall, Humanities Building ---------------------------------------------------------------------------- Course on Uncertain Reasoning Monday, July 27, 1998 Course Registration 7:00-8:10 AM Outside 1100 Grainger Hall (Morgridge Auditorium) Introduction and Goals 8:10-8:15 AM Greg Cooper and Serafin Moral Room 1100 Grainger Hall (Morgridge Auditorium) Using Multi-Agent Systems to Represent Uncertainty 8:15-9:15 AM Joseph Halpern Discussion: 9:15-9:30 AM Break 9:30-9:45 AM Revising and Merging Uncertain Information: An Overview 9:45-10:45 AM Henri Prade Discussion: 10:45-11:00am Partially Observable Markov Decision Processes 11:00-12:00 noon Craig Boutilier Discussion 12:00-12:15 PM Lunch (On you own) 12:15-2:00 PM Learning Causal Relationships from Observational Data 2:00-3:00 PM Peter Spirtes and Richard Scheines Discussion 3:00-3:15 PM Discrete Optimization Problems for Inference in Bayesian Networks 3:15-4:15 PM Dan Geiger Discussion 4:15-4:30 PM Break 4:30-4:45pm The Application of UAI Technology and Methodology to Real-World Problems: A Personal Perspective 4:45-5:45 PM Kazuo Ezawa Discussion 5:45-6:00 PM ========================================================================== 3. European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU'99) First Call for Papers ========================================================================== ECSQARU'99 5-9 July 1999 UCL, London, UK http://www.cs.ucl.ac.uk/staff/a.hunter/ecsqaru AIMS AND SCOPE .............. Uncertainty is in an increasingly important research topic in many areas of computer science. Many formalisms are being developed, with much interest at the theory level directed at developing a better understanding of the formalisms and identifying relationships between formalisms, and at the technology level directed at developing software tools for formalisms and applications of formalisms. The main European forum for the subject is the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU). These have been held in Marsellies (1991), Granada (1993), Fribourg (1995), and Bonn (1997). The next in the series is ECSQARU'99 to be held in London in July 1999. AREAS FOR CONTRIBUTION (not exclusive) ...................................... Default reasoning Belief revision Logics for reasoning with uncertainty Paraconsistent logics Belief functions Bayesian networks Probabilistic reasoning Fuzzy systems Aggregation of arguments Inconsistency handling Decision systems Fusion systems Argumentation systems Applications of uncertainty formalisms Automated reasoning systems for uncertainty Machine learning for uncertainty Theoretical results, algorithms, and applications that address the the unification and integration of different approaches are especially encouraged. PROGRAM COMMITTEE ................. Tony Hunter (London) - Program chair Henri Prade (Toulouse) - Data fusion Finn Jensen (Aalborg) - Bayesian networks Torsten Schaub (Potsdam) - Default systems Philippe Smets (Bruxelles) - Belief functions Dov Gabbay (London) - Logics Rudolf Kruse (Magdeburg) - Fuzzy methods SUBMISSION OF PAPERS .................... Please limit submissions to a maximum of 10 pages, preferrably in LNCS format. Details on the LNCS format, including a Latex .sty file, can be obtained from www.springer.de/comp/lncs/index.html To submit a paper, please send it as a postscript file by email, or post four copies of it, to Tony Hunter at the following address: Tony Hunter Department of Computer Science University College London Gower Street London WC1E 6BT UK Email: a.hunter@cs.ucl.ac.uk Phone: +44 171 380 7295 Fax: +44 171 387 1397 PUBLICATION OF PROCEEDINGS .......................... The proceedings will be published in the Lecture Notes in Computer Science Series, as with all the previous ECSQARU conference proceedings. IMPORTANT DATES ............... Submission deadline 31 January 1999 Notification of acceptance 12 March 1999 CRC for accepted papers 16 April 1999 Workshops and tutorials 5-6 July 1999 Main conference 7-9 July 1999 WORKSHOPS AND TUTORIALS ....................... Additional workshops include: - Fusion in data and knowledge - Agents in an uncertain world - Logic, uncertainty, and information retrieval One-day introductory tutorials include: - Bayesian networks - Belief functions - Default reasoning If you are interested in adding to the workshop or tutorial programme, please contact Simon Parsons (s.d.parsons@qmw.ac.uk). FURTHER INFO ............... For any other queries concerning the conference, please consult the conference web page (www.cs.ucl.ac.uk/staff/a.hunter/ecsqaru) or contact Tony Hunter. ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: ========================================================================== 4. Seventh International Workshop on Artificial Intelligence and Statistics Call for Papers ========================================================================== January 3-6, 1999, Ft. Lauderdale, Florida http://uncertainty99.microsoft.com/ This is the seventh in a series of workshops which has brought together researchers in Artificial Intelligence (AI) and in Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encouraged interdisciplinary work. Papers on all aspects of the interface between AI & Statistics are encouraged. To encourage interaction and a broad exchange of ideas, the presentations will be limited to about 20 discussion papers in single session meetings over three days (Jan. 4-6). Focused poster sessions will provide the means for presenting and discussing the remaining research papers. Papers for poster sessions will be treated equally with papers for presentation in publications. Attendance at the workshop will not be limited. The three days of research presentations will be preceded by a day of tutorials (Jan. 3). These are intended to expose researchers in each field to the methodology used in the other field. The tutorial speakers will include Chris Bishop, Cambridge, Latent variables and neural networks. Sue Dumais, Seattle, Information access and retrieval. and the keynote speaker is David Spiegelhalter, Cambridge, on Bayesian statistical analysis. Topics of Interest: Statistics in AI: vision, robotics, natural language processing, speech recognition AI in statistics: statistical advisory systems, experimental design Automated data analysis Cluster analysis and unsupervised learning Integrated man-machine modeling methods Interpretability in modelling Knowledge discovery in databases Learning Metadata and the design of statistical data bases Model uncertainty, multiple models Multivariate graphical models, belief networks, causal modeling Online analytic processing in statistics Pattern recognition Predictive modelling: classification and regression Probabilistic neural networks Probability and search Statistical strategy Visualization of very large datasets This list is not intended to define an exclusive list of topics of interest. Authors are encouraged to submit papers on any topic which falls within the intersection of AI and Statistics. Submission Requirements: An extended abstract (up to 4 pages) should be emailed (either ascii, word, postscript or a WWW address) to joe.whittaker@lancaster.ac.uk Telephone: +44 (0)1524 593960 or, as a last resort, four paper copies should be mailed to Joe Whittaker Program Chair 7th International Workshop on AI and Statistics Department of Mathematics and Statistics Lancaster University, Lancaster, LA1 4YF, England Submissions will be considered if they are received by midnight July 1, 1998. Please indicate which topic(s) your abstract addresses. Receipt of all submissions will be confirmed via electronic mail. Acceptance notices will be emailed by September 1, 1998. Preliminary papers (up to 20 pages) must be received by November 1, 1998. These preliminary papers will be copied and distributed at the workshop. Program Chairs: David Heckerman, Microsoft, heckerma@microsoft.com Joe Whittaker, Lancaster University, joe.whittaker@lancaster.ac.uk Program Committee: Russell Almond, ETS, Princeton, ralmond@ets.org Chris Bishop, Microsoft Research, Cambridge, cmbishop@microsoft.com Wray Buntine, Thinkbank, Inc., wray@ultimode.com Peter Cheeseman, NASA Ames, cheeseman@kronos.arc.nasa.gov Max Chickering, Microsoft, dmax@microsoft.com Paul Cohen, University of Massachusetts, cohen@cs.umass.edu Greg Cooper, University of Pittsburgh, gfc@smi.med.pitt.edu Phil Dawid, UC, London, dawid@stats.ucl.ac.uk David Dowe, Monash University, David.Dowe@fcit.monash.edu.au William DuMouchel, AT&T, dumouchel@research.att.com Sue Dumais, Microsoft Seattle, sdumais@microsoft.com David Edwards, Novo, DED@novo.dk Doug Fisher, Vanderbilt University, dfisher@vuse.vanderbilt.edu Nir Friedman, Berkeley, nir@cs.berkeley.edu Dan Geiger, Technion, dang@cs.technion.ac.il Edward George, University of Texas, egeorge@mail.utexas.edu Clark Glymour, Carnegie-Mellon University, cg09@andrew.cmu.edu David Hand, Open University, d.j.hand@open.ac.uk Geoff Hinton, University of Toronto, hinton@ai.toronto.edu Tommi Jaakkola, MIT, tommi@life.ai.mit.edu Michael Jordan, Univ. California Berkeley, jordan@cs.berkeley.edu Michael Kearns, AT & T , mkearns@research.att.com Daphne Koller, koller@fiery.stanford.edu Steffen Lauritzen, Aalborg University, steffen@math.auc.dk Hans Lenz, Free University of Berlin, hjlenz@wiwiss.fu-berlin.de David Lewis, AT&T Labs, lewis@research.att.com David Madigan, University of Washington, madigan@stat.washington.edu Andrew Moore, Carnegie-Mellon University, awm@cs.cmu.edu Daryl Pregibon, AT&T Labs, daryl@research.att.com Thomas Richardson, Univ. Wash, tsr@stat.washington.edu, Alberto Roverato, Universita di Modena, roverato@unimo.it Lawrence Saul, AT&T Labs, lsaul@research.att.com Richard Scheines, Carnegie-Mellon University, rs2l+@andrew.cmu.edu Sebastian Seung, Bell Labs, Lucent Technologies, seung@physics.lucent.com Prakash Shenoy, University of Kansas, pshenoy@ukans.edu Padhraic Smyth, JPL and UCI, smyth@sifnos.ics.uci.edu David Spiegelhalter, MRC, Cambridge, david.spiegelhalter@mrc-bsu.cam.ac.uk Peter Spirtes, Carnegie-Mellon University, ps7z@andrew.cmu.edu Milan Studeny, Praha, studeny@utia.cas.cz Nanny Wermuth, Mainz University, wermuth@animal.sowi.uni-mainz.de ========================================================================== 5. Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems - IPMU'98 Proceedings available - table of contents ========================================================================== 7th International Conference IPMU'98 Information Processing and Management of Uncertainty in Knowledge-based Systems Paris, La Sorbonne July 6-10, 1998 Proceedings of IPMU-98 (2 volumes, 2000 pages) can be ordered by sending an email to Bernadette.Bouchon-Meunier@lip6.fr or to Christophe.Marsala@lip6.fr. The price of the proceedings is 400 FF (about 70$). Table of contents / Table des matières Programme Possibility Theory / Théorie des Possibilités Evidence Theory / Théorie de l'évidence Statistics and Probabilities / Statistiques et probabilités Envelopes for Detection and Prediction / Enveloppes pour la détection et la prédiction Fuzzy Preference Modeling and MCDM 1 / Modélisation floue des préférences et décision multicritère 1 Decision Models / Modèles décisionnels Medical Applications of Fuzzy Sets / Applications médicales des ensembles flous Fuzzy Quantities and their Processing / Quantités floues et leur traitement Fuzzy Pattern Analysis / Reconnaissance des formes floues Fuzzy Preference Modeling and MCDM 2 / Modélisation floue des préférences et décision multicritère 2 Trees / Arbres Chaos & Fractals 1 Databases / Bases de données Fuzzy Control 1 / Commande floue 1 Ordinal Operations / Opérations ordinales Decision Trees Under Uncertainty / Arbres de décision sous incertitude Chaos & Fractals 2 Software Reusability 1 / Réutilisation de logiciels 1 Uncertainty in Geospatial Information Systems / Incertitudes dans les systèmes d'information géospatiaux Fuzzy Control 2 / Commande floue 2 Aggregation Operators 1 / Opérateurs d'agrégation 1 Clustering /Regroupement Software Reusability 2 / Réutilisation de logiciels 2 Military Applications / Applications militaires Independence / Indépendance Aggregation Operators 2 / Opérateurs d'agrégation 2 Information Processing in Medecine / Traitement d'informations en médecine Learning / Apprentissage Fuzzy Logic as a Basis for Knowledge Representation in the Natural Science / Logique floue pour la représentation des connaissances dans les sciences naturelles Diagnostic et Fusion / Diagnostic and fusion Probability and Logic of Fuzzy Sets / Probabilités et logique des ensembles flous Measures of Fuzziness and Entropy / Mesures de flou et d'entropie Financial Risk 1 / Risque financier 1 Non-Standard Logics / Logiques non classiques Techniques for Intelligent Information Processing / Techniques pour le traitement intelligent d'information Rough Set Foundations & Methods 1 / Ensembles rugueux, fondements et méthodes 1 Fuzzy Measures 1 / Mesures floues 1 Financial Risk 2 / Risque financier 2 Non Classical Reasoning / Raisonnement non classique Fuzzy Techniques / Techniques floues Rough Set Foundations & Methods 2 / Ensembles rugueux, fondements et méthodes 2 Fuzzy Measures 2 / Mesures floues 2 Soft Computing Causality / Causalité Fuzzy Querying and Information retrieval over the Internet/WWW / Requêtes floues et recherche d'information sur Internet/WWW Rough Set Applications / Applications des ensembles rugueux Fusion Fuzzy Petri Nets / Réseaux de Pétri flous Classification and Recognition / Classification et reconnaissance Traitement d'Incertitude / Uncertainty management Information Measures and Probabilities/ Mesures d'information et probabilités Connectives in Fuzzy Logic / Opérateurs de logique floue Approximate Reasoning / Raisonnement approximatif Artificial Intelligence / Intelligence artificielle Uncertain Environment Management / Gestion d'environnement incertain POSTERS / AFFICHES Author index / Liste des auteurs ************************************************************************** This Newsletter is issued whenever there is new news, and is sent by auto- matic E-mail and without charge to a list of subscribers. 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