Artificial Intelligence and Symbolic Computation: International Conference AISC’98 Plattsburg, New York, USA, September 16–18, 1998 Proceedings

623 Pages·1998·8.23 MB·English

by  Luc De Raedt (auth.)

Lecture Notes in Artificial Intelligence 1476
Subseries of Lecture Notes in Computer Science
Edited by J. G. Carbonell and J. Siekmann
Lecture Notes in Computer Science
Edited by G. Goos, J. Hartmanis and J. van Leeuwen
Jacques Calmet Jan Plaza (Eds.)
laicifitrA Intelligence
dna Symbolic noitatupmoC
International Conference AISC'98
Plattsburgh, New York, USA
September 16-18, 1998
Proceedings
regnirpS
Series Editors
Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, ,AP USA
grOJ Siekmann, University of Saarland, SaarbriJcken, Germany
Volume Editors
Jacques Calmet
Universitat Karlsruhe, Fakult~it Informatik
Am Fasanengarten 5, Postfach 6980, D-76128 Karlsruhe, Germany
E-mail: calmet @ira.uka.de
Jan Plaza
Plattsburgh State University of New York
10l Broad Street, Plattsburgh, NY 12901, USA
E-mail: plazaj a @ splava.cc.plattsburgh.edu
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Die Deutsche Bibliothek - CIP-Einheitsaufnahme
Artificial intelligence and symbolic computation : proceedings /
International Conference AISC '98, Plattsburgh, New York, USA,
September 16 - 18, 1998. Jacques Calmet ; Jan Plaza (ed.). - Berlin ;
Heidelberg ; New York ; Barcelona ; Budapest ; Hong Kong ;
London ; Milan ; Paris ; Singapore ; Tokyo : Springer, 1998
(Lecture notes in computer science ; Vol. 1476 : Lecture notes in
artificial intelligence)
ISBN 3-540-64960-3
CR Subject Classification (1991): 1.2.1-4, 1.1, G.1-2, F.4.1
ISBN 3-540-64960-3 Springer-Verlag Berlin Heidelberg New York
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Foreword
This volume contains invited papers and contributed papers accepted for the
Fourth International Conference on Artificial Intelligence and Symbolic Compu-
tation (AISC'98) held in USA at the Plattsburgh State University of New York
on September 16-18, 1998. The conference belongs to a series that started in
Karlsruhe, Germany in 1992 and continued at King's College, Cambridge, UK
(1994) and in Steyr, Austria (1996). The proceedings of these earlier meetings
appeared in the LNCS series as Volumes 737, 958, and 1138. The first three
conferences were called AISMC, where M stands for "mathematical"; the orga-
nizers of the current meeting decided to drop the adjective "mathematical" and
to emphasize that the conference is concerned with all aspects of symbolic com-
putation in AI: mathematical foundations, implementations, and applications,
including applications in industry and academia.
In the opening paper in the proceedings of AISMC-1, the founders of the -es
ries, J. Calmet and J. Campbell, gave a brief history of the relationship between
artificial intelligence and computer algebra. They also described the scope and
goals of the conferences. The goal was to emphasize the interaction of methods
and problem solving approaches from AI and symbolic mathematical computa-
tion. This year, the conference name has been modified not to exclude mathemat-
ics but to illustrate a broadening of the scope. Mathematics with its universally
accepted language and methodology remains an ideal environment for construct-
ing precise models of symbolic computation in AI. The scope was in fact already
extended in Steyr where the relationship between symbolic mathematical com-
puting and engineering was emphasized. A motivation for extending the scope
comes also from the fact that in recent years research on coupling computing and
deduction systems has flourished. One of the goals of this series of conferences is
to become a forum for such research. This is already exemplified by some of the
papers appearing in this volume. Another goal is to move the center of gravity
from computer algebra and to set it in artificial intelligence. This is also why the
current proceedings are appearing in the LNAI series rather than LNCS.
As in previous conferences, the number of accepted papers has been kept
small. This allows for longer than usual presentations by the authors with enough
time for discussion, and makes it possible to avoid parallel sessions. Such ar-
rangements provide better conditions for exchange of ideas. Since the scope of
the conference is interdisciplinary, this is a mandatory condition to make the
meetings successful and lively.
The site for the next conference is already decided. It will be Madrid, Spain,
in the year 2000.
We gratefully acknowledge the sponsorship of AISC'98 by the Plattsburgh
State University of York. We owe thanks to the members of the Program Com-
mittee and Steering Committee for refereeing contributed papers. Other organi-
zations and individuals who contributed to the conference cannot be listed here
VI Foreword
at the time when these proceedings go to print. We are grateful to them all.
Special thanks go to Christoph Zenger who devoted a lot of time to preparing
the manuscript for this volume.
June 1998 Jacques Calmet and Jan Plaza
Steering Committee
Jacques Calmet (Karlsruhe, Germany)
John Campbell (London, Great Britain)
Jochen Pfalzgraf (Salzburg, Austria)
Jan Plaza (Plattsburgh, USA), Conference Chairman
Program Committee
Francois Arlabosse (Framatome, France)
Bruno Buchberger (Linz, Austria)
Gregory Butler (Montreal, Canada)
Luigia Carlucci Aiello (Rome, Italy)
James Cunningham (London, Great Britain)
John Debenham (Sydney, Australia)
Ruediger Dillmann (Karlsruhe, Germany)
Fausto Giunchiglia (Trento, Italy)
Stan Klasa (Montreal, Canada)
Alfonso Miola (Rome, Italy)
Lin Padgham (Melbourne, Australia)
weingibZ W. Ras (Charlotte, USA)
Klaus U. Schulz (Munich, Germany)
Joerg .H Siekmann (Saarbruecken, Germany)
Andrzej Skowron (Warsaw, Poland)
Stanly Steinberg (Albuquerque, USA)
Karel Stokkermans (Salzburg, Austria)
Carolyn Talcott (Stanford, USA)
Peder Thusgaard Ruhoff (Odense, Denmark)
Dongming Wang (Grenoble, France)
Contents
Invited Talks
An Inductive Logic Programming Query Language for Database Mining
(Extended Abstract) ....................................................
Luc De Raedt
Bertrand Russell, Herbrand's Theorem, and the Assignment Statement ... 14
Melvin Fitting
Representing and Reasoning with Context ................................ 29
Richmond H. Thomason
Regular Talks
From Integrated Reasoning Specialists to "Plug-and-Play" Reasoning
Components ........................................................... 42
Alessandro Armando, Silvio Ranise
Reasoning About Coding Theory: The Benefits We Get from Computer
Algebra ............................................................... 55
Clemens Ballarin, Lawrence C. Paulson
Automatic Generation of Epsilon-Delta Proofs of Continuity ............. 67
Michael Beeson
Finite Model Search for Equational Theories (FMSET) ................... 84
Belaid Benhamou, Laurent Heocque
Specification and Integration of Theorem Provers and Computer Algebra
Systems ............................................................... 94
P.G.Bertoli, J.Calmet, F. Giunchiglia, K.Homann
,ETTELOC Prototyping CSP Solvers Using a Rule-Based Language ...... 107
Carlos Castro
X Contents
An Evolutionary Algorithm for Welding Task Sequence Ordering ........ 021
Martin Damsbo, Peder Thusgaard Ruhoff
Intuitionistic Proof Transformations and Their Application to Constructive
Program Synthesis ................................................... 231
Uwe Egli, Stephan Schmitt
Combining Algebraic Computing and Term-Rewriting for Geometry Theorem
Proving .............................................................. 541
St~phane F~vre, Dongming Wang
Cooperation Between Top-Down and Bottom-Up Theorem Provers by Subgoal
Clause Transfer ...................................................... 751
Dirk Fuchs
Polymorphic Call-by-Value Calculus Based on Classical Proofs
(Extended Abstract) .................................................. 071
Ken-etsu Fujita
Inference and Verification in Medical Appropriateness Criteria Using GrSbner
Bases ................................................................ 381
L.M. Laita, E. Roanes-Lozano, .V Maojo
The Unification Problem for One Relation Thue Systems ................ 591
Christopher Lynch
Basic Completion with E-cycle Simplification ........................... 902
Christopher Lynch, Christelle Scharff
SoleX: A Domain-Independent Scheme for Constraint Solver Extension . 222
Eric Monfroy, Christophe Ringeissen
Optimising Propositional Modal Satisfiability for Description Logic
Subsumption ......................................................... 432
Ian Horrocks, Peter F. Patel-Schneider
Contents XI
Instantiation of Existentially Quantified Variables in Induction Specification
Proofs ............................................................... 247
Brigitte Pientka, Christoph Kreitz
Knowledge Discovery Objects and Queries in Distributed Knowledge
Systems .............................................................. 259
Zbigniew W. Ra~, Jiyun Zheng
ALLTYPES: An ALgebraic Language and TYPE System ................ 072
Fritz Schwarz
Real Parametrization of Algebraic Curves ............................... 482
J. Rafael Sendra, Franz Winkler
Non-clausal Reasoning with Propositional Definite Theories ............. 692
Zbigniew Stachniak
Author Index ......................................................... 903
An Inductive Logic Programming Query
Language for Database Mining
(Extended Abstract)
Luc De Raedt
Department of Computer Science, Katholieke Universiteit Leuven
Celestijnenlaan 200A, B-3001 Heverlee, Belgium
Tel: ++ 32 16 32 76 43 Fax : ++ 32 16 32 79 96
[email protected]
Abstract. First, a short introduction to inductive logic programming
and machine learning is presented and then an inductivedatabase min-
ingquerylanguageRDM(RelationalDatabaseMininglanguage).RDM
integrates concepts from inductive logic programming, constraint logic
programming, deductive databases and meta-programming into a flex-
ible environment for relational knowledge discovery in databases. The
approach is motivated by the view of data mining as a querying pro-
cess (see Imielinkski and Mannila, CACM 96). Because the primitives
ofthepresentedquerylanguage can easily becombinedwith theProlog
programming language, complex systems and behaviour can be speci-
(cid:12)eddeclaratively.Integratingadatabaseminingqueryinglanguagewith
principles of inductive logic programming has the added bene(cid:12)t that it
becomes feasible to search for regularities involving multiple relations
in a database. The proposal for an inductive logic programming query
language putsinductivelogic programming into a new perspective.
Keywords :database mining querylanguage, inductivelogic program-
ming, relational learning, inductivequerylanguage, data mining.
1 Introduction
The(cid:12)rstpartofthe paperprovidesashortintroductionto the(cid:12)eldofinductive
logic programming. Inductive logic programming [20,7] is the study of machine
learning and data mining using the (cid:12)rst order representations o(cid:11)ered by com-
putational logic. Classical approaches to machine learning and data mining use
the so-called attribute-value learning representations, which essentially corre-
spond to propositional logics. The use of computational logic is bene(cid:12)cial for
a variety of reasons. Firstly, inductive logic programming can rely on the the-
ory of logic programming concerning semantics, inference rules, and execution
mechanisms. Secondly, using a richer representation language permits to tackle
applications,whichcannotbehandledbyclassicaltechniques(seee.g.[4,12])for
surveys. Thirdly, the use of computational logic permits to employ background
knowledge in the induction process.
JacquesCalmetandJanPlaza(Eds.):AISC’98,LNAI1476,pp.1{13,1998.
(cid:13)c Springer-VerlagBerlinHeidelberg1998