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UC Irvine ICS Technical Reports UC Irvine ICS Technical Reports Title Working notes of the 1991 spring symposium on constraint-based reasoning Permalink https://escholarship.org/uc/item/5311p0gf Author Dechter, Rina Publication Date 1991-09-16 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Z 63 HoI t, Working Notes of the 1991 Spring Symposium on Constraint-Based Reasoning^ Rina Dechter September 16, 1991 Technical Report 91-65 1991 Spring Symposium Series Constraint-Based Reasoning Working Notes (Distribution limited to symposium attendees) March 26 - 28, 1991 Stanford University Sponsored by the American Association for Artificial Intelligence I WORKING NOTES AAAI SPRING SYMPOSIUM SERIES Symposium; Constraint-Based Reasoning Program Committee: Rina Dechter, UC Irvine, Cochair Sanjay Mittal, Metaphor Computer Systems, Cochair Alan Borning, University of Washington Mark Fox, Carnegie Mellon University Eugene Freuder, University of New Hampshire Joxan Jaffar, IBM T.J. Watson Research Center Alan Mackworth, University of British Columbia Judea Pearl, UC Los Angeles MARCH 26, 27, 28, 1991 STANFORD UNIVERSITY Table of Contents FOREWORJD i Theoretical Issues in Constraint Satisfaction The Logic of Constraint Satisfaction 1 Alan Mackworthj Department of Computer Science, University of British Columbia Constraint-Based Knowledge Acquisition 30 Eugene C. Freuder, Computer Science Department, University of New Hampshire Default Logic, Propositional Logic and Constraints 33 Rachel Ben-Eliyahu, Computer Science Department, University of California, Los Angeles, and Rina Dechter, Department of Information and Computer Science, University of California, Irvine Satisfiability and Reasoning with Inconsistent Beliefs Using Energy Minimization 47 Gadi Pinkas, Computer Science Department, Washington University Reasoning About Disjunctive Constraints 57 Can A. Baykan and Mark S. Fox, The Robotics Institute, Carnegie Mellon University Using Network Consistency to Resolve Noun Phrase Reference 72 Nicholas J. Haddock, Hewlett-Packard Laboratories, Bristol, U. K. Qualitative and Temporal Reasoning Combining QurditatiVe and Quantitative Constraints in Temporal Reasoning 80 Itay Meiri, Computer Science Department, University of California, Los Angeles Integrating Metric and Qualitative Temporal Reasoning 95 Henry Kautz, AT&T Bell Laboratories, and Peter B. Ladkin, International Computer Science Institute Model-Based Temporal Constraint Satisfaction 108 Armen Gabrielian, Thomson-CSF, Inc. Temporal Reasoning with Matrix-Valued Constraints 112 Robert A. Morris and Lina Al-Khatib, Department of Computer Science, Florida Institute of Technology Reason Maintenance and Inference Control for Constraint Propagation over Intervals 122 Walter Hamscher, Price Waterhouse Technology Centre Constraint Logic Programming-1 A Methodology for Managing Hard Constraints in CLP Systems 127 Joxan JalFar, IBM T.J. Watson Research Center, Spiro Michaylov, School of Computer Science, Carnegie Mellon University, and Roland Yap, IBM T.J. Watson Research Center Comparing Solutions to Queries in Hierarchical Constraint Logic Programming Languages 138 Molly Wilson and Alan Borning, Department of Computer Science and Engineering, University of Washington Coping With Nonlinearities in Constraint Logic Programming: Preliminary Results with CLPS(M^ 145 Nairn Abdullah, Michael L. Epstein, Pierre Lim, and Edward H. Freeman, US WEST Advanced Technologies Dataflow Dependency Backtracking in a New CLP Language 150 William S. Havens, Expert Systems Laboratory, Centre for Systems 5ctence, Simon Eraser University Operational Semantics of Constraint Logic Programming over Finite Domains . 168 Pascal Van Hentenryck, Computer Science Department, Brown University, and Yves Deville, University of Namur, Belgium Constructing Hierarchical Solvers for Functional Constraint Satisfaction Problems 187 Sunil Mohan, Department of Computer Science, Rutgers University Distributed and Parallel Constraint Satisfaction Analysis of Local Consistency in Parallel Constraint Satisfaction Networks ..... 194 Simon Kasif and Arthur L. Delcher, Department of Computer Science, The Johns Hopkins University Parallel Path Consistency 204 Steven Y. Susswein, Thomas C. Henderson, and Joe Zachary, Department of Computer Science, University of Utah A Distributed Solution to the Network Consistency Problem 214 Zeev Collin, Computer Science Department, Technion, Israel Institute of Technology, and Rina Dechter, Department of Information and Computer Science, University of California, Irvine Connectionist Networks for Constraint Satisfaction 227 Hans Werner Guesgen, German National Research Center for Computer Science Distributed Constraint Satisfaction for DAI Problems 236 Makoto Yokoo, Artificial Intelligence Laboratory, University of Michigan, Torn Ishida, and Kazuhiro Kuwabara, NTT Communications and Information Processing Laboratories, Japan Constraint Satisfaction in a Connectionist Inference System 245 StelFen HoUdoblet, Universitat Dortmund, Germany Theoretical Issues-2 Directed Constraint Networks: A Relational Framework for Causal Modeling .. 254 Rina Dechter, Department of Information and Computer Science, University of California, Irvine, and Judea Pearl, ComputerScience Department, University of California, Los Angeles The Role of Compilation in Constraint-Based Reasoning 270 Yousri El Fattah and Paul O'Rorke, Department of Information and Computer Science, University of California, Irvine Geometric Constraint Satisfaction Problems 287 Gleim Kramer, Jahir Pabon, Walid Keirouz, and Robert Young, Schlumberger Laboratory for Computer Science Constraint Logic Programming-2 Constraint Imperative Programming Languages 297 Bjorn Freeman-Benson and Alan Borning, Department of Computer Science and Engineering, University of Washington Explaining Constraint Computations 302 Leon Sterling smd Venkatesh Srinivasan, Department of Computer Engineering and Science and Center for Automation and Intelligent Systems Research, Case Western Reserve University Layer Constraints in Hierarchical Fmite Domains 312 Philippe Codognet, INRIA, France, Pierre Saveant, Enrico Maim, and Olivier Briche, SYSECA, France Restriction Site Mapping as a Constraint Satisfaction Problem 321 Roland Yap, IBAf T./. Watson Research Center FOREWORD Constraint-based reasoning (CBR) is a paradigm tbat unifies many traditional area^ in Ar tificial Intelligence. Simply stated, CBR encourages tbe formulation of knowledge in terms of a set of constraints on some entities, without specifying methods for satisfying such con straints. Many techniques for finding partial or complete solutions to constraint expressions have been developed, and have been successfully applied to tasks such as design, diagnosis, truth maintenance, scheduling, spatio-temporal reasoning, and user interface. The symposium brought together a diverse group of researchers, and the work presented spanned many topics, from basic researchand theoretical foundation to practical applications in industrial settings. It became apparent that from a mathematical viewpoint, the field has reached a certain level of maturity; algorithmic breakthroughs were not reported nor were they expected. On the other hand, most of the talks focused on strengthening CBR with new implementation tools or extending the technology to new areas of application. The symposium opened with Alan Mackworth's overview of the interplay between con straint-based reasoning and various logical frameworks. It stressed the point that although constraint satisfaction problems can be expressed in other logical frameworks, the relational language provides a convenient means of encoding knowledge which often invites unique opportunities for efficient processing techniques. The discussions that followed fell into four major categories: 1. Extensions to com- monsense reasoning (default, causal, qualitative, temporal). 2. Parallel and distributed ap proaches, 3. Constraint-logic-programming languages, and 4. New application areas (layout design, natural languages, DNA analysis, mechanical design). 1. The session on commonsense-reasoning centered around issues in temporal reasoning. In particidar, two approaches for combining quantitative temporal specification (e.g., metric networks) and qualitative specification (e.g., Allen's interval algebra) were presented and compared. Meiri (UCLA) treats points and interval as temporal objects of equal status, admitting both qualitative or quantitative relationships. Ladkin (ICSl) and Kautz (BeU Labs) maintain the qualitative and quantitative components in two separate subsystems, and provide sound rules for transforming information between the two. In the area of default reasoning, Ben-Eliyahu (UCLA) and Dechter presented a new tractable class of default theories based on CBR mapping, and Freuder (UNH) discussed an extension of the constraint language that expresses imprecise knowledge. In qualitative rea soning, Kuipers (UT) reviewed issues in qualitativesimulation and the role of constraint pro cessing. This area concludedwith Pearl's (UCLA) presentation of causal constraint networks- a new tractaUe class ofconstraint problem that utilizes the efficiency and modularity inherent to causal organizations. 2. Distributed amd neural architectures for constraint processing received much attention. Kasif (John Hopkins) opened this discussion by surveying the theoretical aspects of parallel computations. We learned that constraint-satisfaction, and even arc-consistency are "non- paraUelisable"
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