close this section of the libraryftp://ftp.daimi.aau.dk (88)
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Constraint Logic Programming: A Bibliography Maintained by: Spiro Michaylov Department of Computer and Information Science The Ohio State University 228 Bolz Hall 2036 Neil Avenue Mall Columbus, OH 43210-1277 U.S.A. December 10, 1992 References A. Aggoun and N. Beldiceanu. Time stamps techniques for
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Using Charme to Represent Protein Structure Constraints Tim Duncan AI Applications Institute, University of Edinburgh, Edinburgh, Scotland. Amr M. El-Said Department of Artificial Intelligence, University of Edinburgh, Edinburgh, Scotland. January 1993 1 Introduction Determining the molecular structure
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/RR-92-17.ps.gz, 19930421
A Feature-based Constraint System for Logic Programming with Entailment Hassan A t-Kaci Andreas Podelski Gert Smolkay
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Implementing Computational Systems with Constraints Claude Kirchner H el ene Kirchner Marian Vittek INRIA-Lorraine & CRIN 615, rue du Jardin Botanique, BP 101 54602 Villers-les-Nancy Cedex FRANCE E-mail: kirchner@loria.fr, vittek@loria.fr
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Records for Logic Programming Gert Smolka Ralf Treinen Deutsches Forschungszentrum fur Kunstliche Intelligenz (DFKI) Stuhlsatzenhausweg 3 D-W6600 Saarbrucken Germany fsmolka,treineng@dfki.uni-sb.de
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DFKI Research Report RR-92-23 Records for Logic Programming Gert Smolka and Ralf Treinen August 1992 Deutsches Forschungszentrum fur Kunstliche Intelligenz GmbH Stuhlsatzenhausweg 3 D-6600 Saarbrucken, Germany Tel.: + 49 (681) 302-5252 Fax: + 49 (681) 302-5341 Records for Logic Programming Gert
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MAX-PLANCK-INSTITUT F UR INFORMATIK Set Constraints are the Monadic Class Leo Bachmair Harald Ganzinger Uwe Waldmann MPI{I{92{240 December 1992 Oo Oo k I N F O R M A T I K Im Stadtwald W 6600 Saarbrucken Germany Authors' Addresses Leo Bachmair Department of Computer Science, SUNY at Stony Brook, Stony
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Solving Geometric Constraint Systems Glenn A. Kramer School of Cognitive and Computing Sciences University of Sussex Brighton BN1 9QH, England Schlumberger Laboratory for Computer Science P.O. Box 200015 Austin, Texas 78720-0015 gak@slcs.slb.com
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A geometric constraint engine 27 References Farhad Arbab and Bin Wang. A constraint-based design system based on operational transformation planning. In J. S. Gero, editor, Proceedings of 4th International Conference on Applications of Artificial Intelligence. Spinger-Verlag, 1989. R. S.
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Default reasoning and the qualitative representation of spatial knowledge y D. Hern andez Institut fur Informatik Technische Universitat Munchen Arcisstr. 21 8000 Munich 2 Fed. Rep. of Germany K. Zimmermann Fachbereich Informatik Universitat Hamburg Bodenstedtstr. 16 2000 Hamburg 50 Fed. Rep. of
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REASONING WITH QUALITATIVE REPRESENTATIONS: EXPLOITING THE STRUCTURE OF SPACE y Daniel Hern andez Fakultat fur Informatik Technische Universitat Munchen Arcisstr. 21, D-8000 Munich 2 e-mail: danher@informatik.tu-muenchen.de
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DFKI Research Report 93-22 Weak Looking-Ahead and its Application to Computer-Integrated Process Planning Manfred A. Meyer and Jorg P. Muller April 1993 Deutsches Forschungszentrum fur Kunstliche Intelligenz GmbH Erwin-Schrodinger-Strasse D-6750 Kaiserslautern, Germany Tel.: + 49 (631) 302-3211
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DFKI Research Report 92-35 Using Hierarchical Constraint Satisfaction for Lathe-Tool Selection in a CIM Environment Manfred Meyer August 1992 Deutsches Forschungszentrum fur Kunstliche Intelligenz GmbH Erwin-Schrodinger-Strasse D-6750 Kaiserslautern, Germany Tel.: + 49 (631) 302-3211 Fax: + 49 (631)
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Constraint Relaxation and Nonmonotonic Reasoning Gerhard Brewka International Computer Science Institute (ICSI) 1947 Center Street, Suite 600, Berkeley, CA 94704-1105, U.S.A. Hans Werner Guesgen, Joachim Hertzbergy German National Research Center for Computer Science (GMD) Artificial Intelligence
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Page 1 of 5 Optimization techniques for nondeterministic promotion in the Andorra Kernel Language Extended abstract Remco Moolenaar and Bart Demoen Department of Computer Science Celestijnenlaan 200 A, 3001 Heverlee, Belgium e-mail: {remco, bimbart}@cs.kuleuven.ac.be In this extended abstract some
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1 to appear in Int. Journal of Expert Systems: Research and Applications, JAI Press, Dec. 1992. Intelligent Backtracking in the Echidna Constraint Logic Programming System William S. Havens Expert Systems Laboratory School of Computing Science and Centre for Systems Science Simon Fraser University
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technical report ECRC{92{1 Generalised Constraint Propagation Over the CLP Scheme Thierry Le Provost Mark Wallace EUROPEAN COMPUTER-INDUSTRY RESEARCH CENTRE ECRC GMBH, ARABELLASTR. 17 D-8000 MUNCHEN 81, GERMANY - TEL +49 89/926 99 - FAX 926 99 170 - TLX 521 6910 c European Computer-Industry Research
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Proceedings of the 1993 International Logic Programming Symposium, MIT Press A Practical Approach to the Global Analysis of CLP Programs M. Garc a de la Banda M. Hermenegildo Facultad de Inform atica Universidad Polit ecnica de Madrid (UPM) 28660-Boadilla del Monte, Madrid - Spain
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LISP AND SYMBOLIC COMPUTATION: An International Journal, 5, 223{270, 1992 c 1992 Kluwer Academic Publishers { Manufactured in The Netherlands Constraint Hierarchies ALAN BORNING (borning@cs.washington.edu) Department of Computer Science and Engineering, FR-35, University of Washington, Seattle,
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Hierarchical Constraint Logic Programming Molly Wilson and Alan Borning Technical Report 93-01-02a Department of Computer Science and Engineering University of Washington May 1993
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Integrating Constraints with an Object-Oriented Language Bjorn N. Freeman-Benson University of Victoria Department of Computer Science P.O. Box 3055 Victoria, B.C., V8W 3P6, CANADA bnfb@csr.uvic.ca Alan Borning Department of Computer Science and Engineering, FR-35 University of Washington Seattle,
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/EAAS.ps.gz, 19930803
Solving Space Planning Problems Using Constraint Technology Philippe CHARMAN SECOIA Project CERMICS-INRIA 2004, route des Lucioles BP 93 06902 SOPHIA-ANTIPOLIS Cedex Email: charman@snoopy.inria.fr Tel: 93.65.77.48
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DFKI Research Report 93-39 Constraint Processing Proceedings of the International Workshop at CSAM'93 Manfred Meyer (Ed.) August 1993 Deutsches Forschungszentrum fur Kunstliche Intelligenz GmbH Postfach 20 80 D-67608 Kaiserslautern, FRG Tel.: + 49 (631) 205-3211 Fax: + 49 (631) 205-3210
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/natobook/matijasevich.ps.gz, 19940121
2.4 Interval Computations as Propagation of Constraints Yuri Matiyasevich Steklov Institute of Mathematics of Russian Academy of Sciences Saint-Petersburg Branch (POMI RAN) 27 Fontanka, Saint-Petersburg, 191011, Russia yuma@Lomi.spb.su 2.4.1 The Problem Suppose that we have a program P written in some
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2.5 Applying Constraints for Scheduling Mark Wallace Institute European Computer-Industry Research Centre Arabellastr 17, 8000 M unchen 81 Germany Mark.Wallace@ecrc.de 2.5.1 Introduction Scheduling problems come in all shapes and sizes, and no two problems are alike. However it is possible to abstract
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4.2 Constraints in NUT Jaan Penjam Institute of Cybernetics, Akadeemia tee 21, EE0026 Tallinn, Estonia Enn T~ougu Inst f or Teleinformatik, Kungl Tekniska H ogskolan, Electrum 204, S-16440 KISTA, Sweden
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1. Introduction 1.1 Constraint Satisfaction and Constraint Programming: A Brief Lead-In Brian Mayoh and Enn Tyugu and Tarmo Uustalu Aarhus University, Computer Science Dept, Ny Munkegade 540, DK-8000 Aarhus, Denmark and The Royal Institute of Technology, Dept of Teleinformatics, Electrum 204, S-164 40
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1.2 Constraint Programming and Artiflcial Intelligence Brian Mayoh Computer Science Department Aarhus University Ny Munkegade, Bldg. 540, 8000 Aarhus C Denmark brian@daimi.aau.dk There is a symbiosis between artiflcial intelligence (AI) and constraint programming (CP). In this chapter we will describe
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3.3 Denotational Semantics of Constraint Logic Programming { A Nonstandard Approach Erik Palmgren1 Department of Mathematics, Uppsala University PO Box 480, S-751 06 Uppsala, Sweden palmgrem@bellatrix.tdt.uu.se 3.3.1 Introduction Ideas and results from logic are continually put to use within the fleld
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3.4 Resolution Strategies for the Intuitionistic Logic Grigori Mints Department of Philosophy, Stanford University Stanford, CA 94305 mints@csli.stanford.edu This paper presents a general scheme of transforming a cutfree Gentzen-type system into a resolution type system, preserving the structure of
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1 2.3 Higher-Order Functional Constraint Networks Enn Tyugu and Tarmo Uustalu The Royal Institute of Technology Dept of Teleinformatics Electrum 204 S-164 40 Kista, Sweden tyugu j tarmo@it.kth.se This paper discusses value propagation on functional constraint networks. We flrst focus on conventional
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2. Constraint Solving Techniques 2.1 Exploiting Structure in Constraint Satisfaction Problems Eugene C. Freuder Department of Computer Science University of New Hampshire Durham, New Hampshire 03824 USA ecf@cs.unh.edu 2.1.1 Introduction Constraint satisfaction problems (CSPs) involve flnding values for
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3. Foundations of Constraint Programming Approaches 3.1 Concurrent Semantics for Concurrent Constraint Programs Francesca Rossi and Ugo Montanari University of Pisa Computer Science Department Corso Italia 40 56125 Pisa, Italy fugo,rossig@di.unipi.it
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2.2 Constraint Hierarchies Alan Borning, Bjorn Freeman-Benson, and Molly Wilson Dept. of Computer Science & Engineering, FR-35 University of Washington Seattle, Washington 98195 USA borning@cs.washington.edu This paper was originally published in Lisp and Symbolic Computation, Vol. 5 No. 3, (September
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4. Constraint Programming Systems 4.1 Kaleidoscope: A Constraint Imperative Programming Language Gus Lopez, Bjorn Freeman-Benson, and Alan Borning Gus Lopez and Alan Borning Bjorn Freeman-Benson Dept. of Computer Science & Engineering, FR-35 School of Computer Science University of Washington Carleton
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4.5 An Introduction to AKL A Multi-Paradigm Programming Language Sverker Janson and Seif Haridi Swedish Institute of Computer Science Box 1263, S-164 28 KISTA, Sweden E-mail sverker@sics.se, seif@sics.se 4.5.1 Introduction AKL is a multi-paradigm programming language based on a concurrent constraint
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Contents 1. Introduction 1.1 Constraint Satisfaction and Constraint Programming: A Brief Lead-In B. Mayoh, E. Tongu and T. Uustalu : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 1 1.2 Constraint Programming and Artiflcial Intelligence B. Mayoh : : : : : : : : : : : : : : : : : : : : : :
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4.3 Interval Constraint Programming in C++ Eero Hyv}onen, Stefano De Pascale and Aarno Lehtola VTT, Technical Research Centre of Finland Information Systems P.O.Box 1201, 02044 VTT, Finland feero.hyvonen j stefano.depascale j aarno.lehtola g@vtt.fl
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4.4 Programming in Timed Concurrent Constraint Languages Vijay Saraswat, Radha Jagadeesan and Vinheet Gupta Loyola College Stanford University U.S.A. saraswat@parc.xerox.com 4.4.1 Introduction The areas of Qualitative Reasoning about physical systems (Weld and de Kleer 1989), reasoning about action and
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CLP(CF) Constraint Logic Programming over Complex Functions Hoon Hong Research Institute for Symbolic Computation Johannes Kepler University A-4040 Linz, Austria e-mail: hhong@risc.uni-linz.ac.at
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Confluency of Cooperative Constraint Solvers Hoon Hong Research Institute for Symbolic Computation Johannes Kepler University A-4040 Linz, Austria e-mail: hhong@risc.uni-linz.ac.at January 16, 1994
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Preface Constraint programming paradigm is based on the idea to manipulate objects using available partial information. The concept of constraint programming was introduced in artificial intelligence and graphics in 60's and 70's. Now the related techniques are used and studied in many fields of
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Untyped Constrained Lambda Calculus is Weakly Church Rosser John N. Crossley Monash University, Melbourne, Australia. jnc@bruce.cs.monash.edu.au Luis Mandely FORWISS, Munchen, Germany. mandel@forwiss.tu-muenchen.de Martin Wirsingz Ludwig-Maximilians-Universitat, Munchen, Germany.
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List of participants Nicolaos ANGELOPOULOS Imperial College Dept. of Computing Huxley Building 180 Queens Gate London SW7-2BZ UNITED KINGDOM Email: na3@doc.ic.ac.uk Francisco A. AZEVEDO Universidade Nova de Lisboa FCT Dpto. de Informatica 2825 Monte Caparica PORTUGAL Fax: +351 1 295 5641 Email:
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Constraints Specification for Task Scheduling in Real-Time Systems Carlos Cardeira 12, Zoubir Mammeri34 and Jean-Pierre Thomesse4 1 Sistemas { DEM { Instituto Superior T ecnico Avenida Rovisco Pais, P1096 Lisboa Codex, Portugal D2462@ist.utl.pt 2 CRAN (Centre de Recherche en Automatique de Nancy) Ensem,
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Real-Time Semantics for Concurrent Logic Languages Tony Savor, Paul Dasiewicz (tsavor@vlsi.uwaterloo.ca, dasiewic@vlsi.uwaterloo.ca) Department of Electrical and Computer Engineering University of Waterloo Waterloo, Ontario, Canada N2L 3G1
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The Framework for Specification of Conceptual Constraints in Data Engineering Remigijus Gustas Kaunas University of Technology, Information Systems Department e-mail REMIGIJUS.GUSTAS@IF.KTU.LT
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On the Decomposition of Hypergraphs Peter Jeavons, David Cohen Department of Computer Science Royal Holloway, University of London Egham, Surrey TW20 0EX, UK Marc Gyssens Department WNI University of Limburg B-3590 Diepenbeek, Belgium
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Disjunctive Constraints as Generalization of Finite Domains Andrei Mantsivoda Department of Mathematics Irkutsk University Irkutsk 664003 Russia email: kvantor@glas.apc.org
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Solving Linear Diophantine Equations Ana Paula Tom as, Miguel Filgueiras LIACC, Universidade do Porto R. do Campo Alegre 823, 4100 Porto, Portugal email: apt@ncc.up.pt, mig@ncc.up.pt
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Constraint Satisfaction Problem as a Causal Theory Robert Rodo<=sek University of Munich, Department of Computer Science Theresienstrasse 39, 80333 Munich, Germany rodosek@informatik.uni-muenchen.de
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Using the intrinsic structure of relational domains to improve constraint propagation and relaxation procedures Daniel Hern andez Fakultat fur Informatik Technische Universitat Munchen 80290 Munich, Germany e-mail: danher@informatik.tu-muenchen.de
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Constraint Propagation in Subdefinite Models V.V. Telerman (Russian Research Institute of Artificial Intelligence, Novosibirsk Division) pr. Lavrent'eva 6, Novosibirsk, Russia, 630090 e-mail vtel@isi.itfs.nsk.su
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Integration of Different Knowledge Representation Means in Knowledge Bases T.M. Yakhno (Institute of Informatics Systems , Russian Academy of Science, Siberian Division) pr. Lavrent'eva 6, Novosibirsk, Russia, 630090 e-mail yakhno@isi.itfs.nsk.su
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1 Solving Space Planning Problems Using Constraint Technology Philippe CHARMAN SECOIA Project CERMICS-INRIA 2004, route des Lucioles BP 93 06902 SOPHIA-ANTIPOLIS Cedex Email: charman@snoopy.inria.fr Tel: 93.65.77.48
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/ESTproceed/cleary.ps, 19940127
Proving the Existence of Solutions in Logical Arithmetic John G.Cleary University of Waikato, Hamilton, New Zealand email: jcleary@waikato.ac.nz
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INSTITUTE OF CYBERNETICS Estonian Academy of Sciences B.Mayoh, J.Penjam, E.Tyugu (Eds.) NATO Advanced Study Institute CONSTRAINT PROGRAMMING August 13 - 24, 1993 Parnu, Estonia Students' presentations Technical Report CS 57/93 Tallinn ffl 1993 ISBN 9985-50-046-6 c Institute of Cybernetics of Estonian
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2. Constraint Solving Techniques 2.1 Exploiting Structure in Constraint Satisfaction Problems Eugene C. Freuder Department of Computer Science University of New Hampshire Durham, New Hampshire 03824 USA ecf@cs.unh.edu 2.1.1 Introduction Constraint satisfaction problems (CSPs) involve flnding values for
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/ESTproceed/maslov.ps, 19940127
From Competition to Amalgamation of Different Programming Paradigms Sergei G. Maslov Udmurt University Dept. of Mathematics & Computer Science Russia p.c.: 426011, city: Izhevsk, 275-61 Udmurtskay str. e-mail: miss@matsim.udmurtia.su, Fax: 3412 75 15 18 NATO ASI Constraint Programming August 13-24 93
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Modular Confluency of Cooperative Constraint Solvers Hoon Hong Research Institute for Symbolic Computation Johannes Kepler University A-4040 Linz, Austria e-mail: hhong@risc.uni-linz.ac.at February 9, 1994
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J. LOGIC PROGRAMMING: to appear 1 Constraint Logic Programming: A Survey Joxan Jaffar and Michael J. Maher Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Though a relatively new field, CLP has progressed in several quite different
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internal report ECRC{92{6i Constraint Logic Programming An Informal Introduction Thom Fruhwirth, Alexander Herold, Volker Kuchenhoff, Thierry Le Provost, Pierre Lim, Eric Monfroy, Mark Wallace EUROPEAN COMPUTER-INDUSTRY RESEARCH CENTRE ECRC GMBH, ARABELLASTR. 17 D-8000 MUNCHEN 81, GERMANY - TEL +49
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technical report ECRC{92{18 Constraint Simplification Rules Thom Fruhwirth thom@ecrc.de EUROPEAN COMPUTER-INDUSTRY RESEARCH CENTRE ECRC GMBH, ARABELLASTR. 17 D-8000 MUNCHEN 81, GERMANY - TEL +49 89/926 99 - FAX 926 99 170 - TLX 521 6910 c European Computer-Industry Research Centre, February 1993
open this document and view contentsftp://ftp.daimi.aau.dk/pub/CLP/tr_genprop.ps.gz, 19940317
technical report ECRC{92{1 Generalised Constraint Propagation Over the CLP Scheme Thierry Le Provost Mark Wallace EUROPEAN COMPUTER-INDUSTRY RESEARCH CENTRE ECRC GMBH, ARABELLASTR. 17 D-8000 MUNCHEN 81, GERMANY - TEL +49 89/926 99 - FAX 926 99 170 - TLX 521 6910 c European Computer-Industry Research
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Two Problems - Two Solutions: One System - ECLiPSe Mark Wallace and Andr e Veron April 1993 1 Introduction The constraint logic programming system ECLiPSe is the successor to the CHIP system . Computation in ECLiPSe alternates between two modes: constraint handling and host program execution. The
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technical report ECRC{93{5 Constraint Logic Programming An Informal Introduction Thom Fruhwirth, Alexander Herold, Volker Kuchenhoff, Thierry Le Provost, Pierre Lim, Eric Monfroy, Mark Wallace EUROPEAN COMPUTER-INDUSTRY RESEARCH CENTRE ECRC GMBH, ARABELLASTR. 17 D-8000 MUNCHEN 81, GERMANY - TEL +49
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Technical Report ECRC-94-05 February 16, 1994 Temporal Reasoning with Constraint Handling Rules Thom Fruhwirth thom@ecrc.de European Computer-Industry Research Centre GmbH Arabellastr. 17, D-81925 Munchen Germany
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Domain Independent Propagation Thierry Le Provost, Mark Wallace ECRC, Arabellastr 17 8000 Munchen 81, Germany fthierry j markg@ecrc.de
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Timetabling in Constraint Logic Programming Francisco Azevedo Pedro Barahona (fa@fct.unl.pt) (pb@fct.unl.pt) Departamento de Inform atica, Universidade Nova de Lisboa 2825 Monte da Caparica | Portugal
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Characterization of the set of models by means of symmetries Lakhdar Sais Laboratoire d'Informatique de Marseille URA CNRS 1787 Universit e de Provence, UFR-MIM 3, place Victor Hugo 13331 Marseille Cedex 3 FRANCE E-mail: sais@gyptis.univ-mrs.fr
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Beyond Finite Domains Joxan Jaffar Michael J. Maher Peter J. Stuckeyy Roland H.C. Yapy 1 Introduction A finite domain constraint system can be viewed as an linear integer constraint system in which each variable has an upper and lower bound. Finite domains have been used successfully in Constraint Logic
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Encapsulated Search and Constraint Programming in Oz Christian Schulte, Gert Smolka, and Jorg Wurtz German Research Center for Artificial Intelligence (DFKI) Stuhlsatzenhausweg 3, D{66123 Saarbrucken, Germany fschulte,smolka,wuertzg@dfki.uni-sb.de
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Logic-Based Methods for Optimization J. N. Hooker Graduate School of Industrial Administration Carnegie Mellon University, Pittsburgh, PA 15213 USA March 1994
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A Substitution Operation for Constraints Peter Jeavons, David Cohen Department of Computer Science Royal Holloway, University of London, UK Martin Cooper IRIT, University of Toulouse III, France March 30, 1994
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Locally Simultaneous Constraint Satisfaction Hiroshi Hosobe y Ken Miyashitay Shin Takahashiy Satoshi Matsuokaz Akinori Yonezaway yDepartment of Information Science, University of Tokyo zDepartment of Mathematical Engineering, University of Tokyo
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GSAT and Dynamic Backtracking Matthew L. Ginsberg CIRL 1269 University of Oregon Eugene, OR 97403 David A. McAllester MIT AI Laboratory 545 Technology Square Cambridge, MA 02139
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Specification and Verification of Constraint-Based Dynamic Systems Ying Zhang Department of Computer Science University of British Columbia Vancouver, B.C. Canada V6T 1Z4 zhang@cs.ubc.ca Alan K. Mackworth Department of Computer Science University of British Columbia Vancouver, B.C. Canada V6T 1Z4
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CC Programs with both In- and Non-determinism: A Concurrent Semantics Ugo Montanari Francesca Rossi Vijay Saraswaty
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Some Remarks on the Design of Constraint Satisfaction Problems Massimo PALTRINIERI Bull Rue Jean Jaur s - B.P. 68 78340 Les Clayes Sous Bois France
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No-good backmarking with min-conflict repair in constraint satisfaction and optimization Yuejun Jiang1, Thomas Richards2 and Barry Richards IC-Parc Imperial College London SW7 2BZ, England fyj, etr, ebrg@uk.ac.ic.doc
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Linear vs. Polynomial Constraints in Database Query Languages Foto Afratiz NTU Athens Stavros S. Cosmadakis New York University St ephane Grumbachx I.N.R.I.A. Gabriel M. Kuper ECRC
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Efficient and Complete Tests for Database Integrity Constraint Checking Ashish Gupta Yehoshua Sagivy Jeffrey D. Ullman Jennifer Widom Department of Computer Science Stanford University Stanford, CA 94305-2140 fagupta,sagiv,ullman,widomg@cs.stanford.edu 1 Introduction An important feature of modern
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Constraint Arithmetic on Real Intervals William Older Andr e Vellino
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Constraint Logic Programming on Boolean, Integer and Real Intervals Fr ed eric Benhamou , William J. Older and Andr e Vellinoy Accepted for publication in Journal of Symbolic Computation September 21, 1994
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Extending Prolog with Constraint Arithmetic on Real Intervals William Older Andr e Vellino Computing Research Laboratory Bell-Northern Research P.O. Box 3511, Station C K1Y 4H7, Ottawa, Ontario
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Specialization in Populations of Artificial Neural Networks. Henrik Hautop Lund x{ Brian H. Mayoh x x DAIMI University of Aarhus, Ny Munkegade, 8000 Aarhus C., Denmark tel.: (+45) 89 42 32 21 fax : (+45) 89 42 32 55 { Institute of Psychology National Research Council, Viale Marx 15, 00137 Rome, Italy