Table Of ContentLecture Notes in Artificial Intelligence 4369
EditedbyJ.G.CarbonellandJ.Siekmann
Subseries of Lecture Notes in Computer Science
Masanobu Umeda Armin Wolf
Oskar Bartenstein Ulrich Geske
Dietmar Seipel Osamu Takata (Eds.)
Declarative Programming
for Knowledge Management
16thInternationalConferenceonApplications
ofDeclarativeProgrammingandKnowledgeManagement,INAP2005
Fukuoka,Japan,October22-24,2005
RevisedSelectedPapers
1 3
SeriesEditors
JaimeG.Carbonell,CarnegieMellonUniversity,Pittsburgh,PA,USA
JörgSiekmann,UniversityofSaarland,Saarbrücken,Germany
VolumeEditors
MasanobuUmeda
KyushuInstituteofTechnology
680-4Kawazu,Iizuka,Fukuoka820-8502,Japan
E-mail:[email protected]
ArminWolf
UlrichGeske
FraunhoferFIRST
Kekuléstraße7,12489Berlin,Germany
E-mail:{armin.wolf,ulrich.geske}@first.fraunhofer.de
OskarBartenstein
IFComputerJapan
5-28-2Sendagi,Bunkyo-ku,Tokyo113-0022,Japan
E-mail:[email protected]
DietmarSeipel
UniversitätWürzburg
AmHubland,97074Würzburg,Germany
E-mail:[email protected]
OsamuTakata
KyushuInstituteofTechnology
680-4Kawazu,Iizuka,Fukuoka820-8502,Japan
E-mail:[email protected]
LibraryofCongressControlNumber:2006938800
CRSubjectClassification(1998):I.2.4,I.2,D.1.6
LNCSSublibrary:SL7–ArtificialIntelligence
ISSN 0302-9743
ISBN-10 3-540-69233-9SpringerBerlinHeidelbergNewYork
ISBN-13 978-3-540-69233-1SpringerBerlinHeidelbergNewYork
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Preface
Knowledge means power – but only if it is available at the right time, the right
place, and in the hands of the right people. Structured, engineered, repeatable
methodstogather,transport,andapplyknowledgearecollectivelycalledknowl-
edge management.
Declarative programming strives for the ideal of programming by wish: the
user states what he or she wants, and the computer figures out how to achieve
it. Thus, declarative programming splits into two separate parts: methods for
humans on how to write wishes, and algorithms for computers that fulfil these
wishes.
Knowledgemanagementisnowrecognizedasaneconomickeyfactor.Declar-
ative programming has matured far beyond the research stage of a merely in-
teresting formal logic model to one of the powerful tools in computer science.
Nowadays,noprofessionalactivityisthinkablewithoutknowledgemanagement,
and companies increasingly need to document their business processes. Here,
declarative programmingcarries the promise to be a shortcut to not only docu-
menting but also implementing knowledge-basedenterprises.
This volume presents a selection of papers presented at the 16th Interna-
tional Conference on Applications of Declarative Programming and Knowledge
Management,INAP 2005,heldinOctober2005atWasedaUniversity,Fukuoka,
Japan. These papers reflect a snapshot of ongoing research and current appli-
cations in knowledge management and declarative programming. Further, they
provide reality checks and many pointers for readers who consider introducing
related technologies into their products or working environments.
Skimming throughthe table of contents, technology managersas well as im-
plementorswillbesurprisedonthewidescopecoveredbythisselectionofpapers.
If you think of knowledge streams as supply, manufacturing, or distribution
chains, you will see that it all fits together.
Thepapershavebeenselectedfortheirthought-provokingvalue,theauthors
are aware that their readers have diverse backgrounds. We sincerely hope that
this book is stimulating reading, applying and conducting further research in
declarative programming and knowledge management.
Japan/Germany 2006 Masanobu Umeda
Armin Wolf
Oskar Bartenstein
Ulrich Geske
Dietmar Seipel
Osamu Takata
(Editors)
Organization
INAP2005wasorganizedbyIFComputer,Japan,theKyushuInstituteofTech-
nology,Japan,FraunhoferFIRST,Germany,UniversityofWu¨rzburg,Germany,
and Waseda University, Japan.
Executive Committee
Conference Chair: Oskar Bartenstein
IF Computer, Japan
ProgramCo-chair: Masanobu Umeda
Kyushu Institute of Technology, Japan
ProgramCo-chair: Armin Wolf
Fraunhofer FIRST, Germany
Constraints Track Chair: Ulrich Geske
Fraunhofer FIRST, Germany
Knowledge Management Track Chair: Dietmar Seipel
University of Wu¨rzburg, Germany
Applications Track Chair: Osamu Takata
Kyushu Institute of Technology, Japan
Local Arrangement Chair: Osamu Yoshie
Waseda University, Japan
Program Committee
Masanobu Umeda, Kyushu Institute of Technology, Japan
Armin Wolf, Fraunhofer FIRST, Germany
Oskar Bartenstein, IF Computer, Japan
Ulrich Geske, Fraunhofer FIRST, Germany
Dietmar Seipel, University of Wu¨rzburg, Germany
Osamu Yoshie, Waseda University, Japan
Osamu Takata, Kyushu Institute of Technology, Japan
Kouichi Shibao, AIE Research, Japan
Virginia Dignum, Utrecht University, Netherlands
Petra Hofstedt, Technical University of Berlin, Germany
Neng-Fa Zhou, The City University of New York, USA
Sergio A. Alvarez, Boston College, USA
Joachim Baumeister, University of Wu¨rzburg, Germany
Carolina Ruiz, Worcester Polytechnic Institute, USA
VIII Organization
External Referees
Masaaki Hashimoto, Kyushu Institute of Technology, Japan
Hidenobu Kunichika, Kyushu Institute of Technology, Japan
Keiichi Katamine, Kyushu Institute of Technology, Japan
NaoyasuUbayashi, Kyushu Institute of Technology, Japan
Taketoshi Ushiama, Kyushu University, Japan
Andreas Bo¨hm, University of Wu¨rzburg, Germany
Marbod Hopfner, University of Wu¨rzburg, Germany
Supporting Institutions
IF Computer, Tokyo, Japan
Waseda University, Graduate School of Information, Production and Systems,
Japan
Table of Contents
Frontier Technologies
Prolog Cafe: A Prolog to Java Translator System..................... 1
Mutsunori Banbara, Naoyuki Tamura, and Katsumi Inoue
TURTLE++ – A CIP-Library for C++ ............................. 12
Petra Hofstedt and Olaf Krzikalla
Constraint Solving for Sequences in Software Validation and
Verification ..................................................... 25
Nikolai Kosmatov
Using a Logic Programming Language with Persistence and Contexts... 38
Salvador Abreu and Vitor Nogueira
On a Rough Sets Based Data Mining Tool in Prolog:An Overview .... 48
Hiroshi Sakai
Not-First and Not-Last Detection for Cumulative Scheduling
in O(n3logn) ................................................... 66
Andreas Schutt, Armin Wolf, and Gunnar Schrader
Calc/Cream: OpenOffice Spreadsheet Front-End for Constraint
Programming.................................................... 81
Naoyuki Tamura
O(nlogn) Overload Checking for the Cumulative Constraint and Its
Application ..................................................... 88
Armin Wolf and Gunnar Schrader
Inductive Logic Programming:Yet Another Application of Logic....... 102
Akihiro Yamamoto
Industrial Case Studies
Railway Scheduling with Declarative Constraint Programming......... 117
Ulrich Geske
User Profiles and Matchmaking on Mobile Phones.................... 135
Thomas Kleemann and Alex Sinner
X Table of Contents
A Design Product Model for Mechanism Parts by Injection Molding.... 148
Tatsuichiro Nagai, Isao Nagasawa, Masanobu Umeda,
Tatsuji Higuchi, Yasuyuki Nishidai, Yusuke Kitagawa,
Tsuyoshi Tsurusaki, Masahito Ohhashi, and Osamu Takata
A Knowledge-Based System for Process Planning in Cold Forging
Using the Adjustment of Stepped Cylinder Method................... 161
Osamu Takata, Yuji Mure, Yasuo Nakashima, Masuharu Ogawa,
Masanobu Umeda, and Isao Nagasawa
Business Integration
An Overview of Agents in Knowledge Management................... 175
Virginia Dignum
ubiCMS – A Prolog Based Content Management System.............. 190
Oskar Bartenstein
Multi-threading Inside Prolog for Knowledge-Based Enterprise
Applications..................................................... 200
Masanobu Umeda, Keiichi Katamine, Isao Nagasawa,
Masaaki Hashimoto, and Osamu Takata
A Meta-logical Approach for Multi-agent Communication of Semantic
Web Information................................................. 215
Visit Hirankitti and Vuong Xuan Tran
Author Index.................................................. 229
Prolog Cafe: A Prolog to Java Translator System
Mutsunori Banbara1, Naoyuki Tamura1, and Katsumi Inoue2
1 Information Scienceand Technology Center, Kobe University
1-1 Rokkodai, Nada, Kobe 657-8501, Japan
{banbara, tamura}@kobe-u.ac.jp
2 National Instituteof Informatics
2-1-2 Hitotsubashi, Chiyoda-ku,Tokyo101-8430, Japan
[email protected]
Abstract. We present the Prolog Cafe system that translates Prolog
into Javavia theWAM. Prolog Cafe providesmulti-threaded Prolog en-
gines. A Prolog Cafe thread seems to be conceptually an independent
PrologevaluatorandcommunicateswitheachotherthroughsharedJava
objects. Prolog Cafe also has theadvantages of portability, extensibility,
smooth interoperation with Java, and modularity. In performance, our
translator generates faster code for a set of classical Prolog benchmarks
than an existing Prolog-to-Java translator jProlog.
1 Introduction
Recent development of Prolog in Java suggests a successful direction to extend
not only Prolog to be more networked and mobile, but also Java applications
to be more intelligent. We aim to develop a Java-conscious Prolog system that
hasthe advantagesofportability,extensibility,interoperability,parallelism,and
modularity.
In the implementation of Prolog,the Warren Abstract Machine (WAM) [1,2]
has became a de facto standard. WAM is flexible enough for several exten-
sionssuchashigher-order,concurrent,constraint,andlinearlogicprogramming.
WAM has been also a basis for compiling Prolog into C [3], C++, Java, C#.
We present the Prolog Cafe system that translates Prolog into Java. The
execution model of translatedJava classes is basedon the WAM. Main features
of Prolog Cafe are as follows:
– Portability
Prolog Cafe is a 100% pure Java implementation and is portable to any
platform supporting a Java compiler.
– Extensibility
The output of Prolog Cafe translator can be well structured and readable.
PrologCafeisthereforeeasilyexpandablewithincreasingJavaclasslibraries.
– Interoperability
FromtheJavaside,thetranslatedcodeofPrologCafecanbeeasilyembedded
into Java applications such as Applets and Servlets. From the Prolog side,
any Java object can be represented as a Prolog term, and its methods and
fields can be exploited from Prolog.
M.Umedaetal.(Eds.):INAP2005,LNAI4369,pp.1–11,2006.
(cid:2)c Springer-VerlagBerlinHeidelberg2006
2 M. Banbara, N. Tamura, and K.Inoue
– Parallelism
Prolog Cafe provides multi-threaded Prolog engines. A Prolog Cafe thread
seemstobeconceptuallyanindependentPrologevaluator,inwhichaProlog
goalruns ona localruntime environment.PrologCafe threadscommunicate
with each other through shared Java objects.
– Modularity
Prolog modules are translated into separate Java packages that can be im-
ported from each other.
Inperformance,ourtranslatorgeneratesfastercodeforasetofclassicalProlog
benchmarksthananexistingProlog-to-JavatranslatorjProlog.Maindifferences
from the previous versionof Prolog Cafe [4] are new features of interoperability,
parallelism, and modularity listed above.
UsefulnessofPrologCafehasbeenshownthroughseveralapplications:P#[5],
Multisat [6], Maglog [7], Holoparadigm [8], and CAWOM [9]. Among these appli-
cations,we give a brief introduction to the Multisat system,a parallelexecution
system of SAT solvers.
The reminder ofthis paperis organizedasfollows.After showingthe transla-
tionmethodofexistingPrologtoJavatranslatorsinSection2,Section3presents
the Prolog Cafesystemin detail.Relatedworkis discussed inSection4,andthe
paper is concluded in Section 5.
2 Existing Prolog to Java Translator Systems
Inthis section,we presenthowjPrologandLLPjtranslateProloginto Java.Due
to space limitations, we use the following simple example:
p :- q, r.
q.
2.1 jProlog
The jProlog [10] system, developed by B. Demoen and P. Tarau, is a first gen-
erationPrologto Javatranslatorvia the WAM. jPrologis basedon binarization
transformation [11], a continuation passing style compilation used in BinProlog.
In jProlog approach, each clause is first translated into a binary clause by
binarization and then translated into one Java class. Each predicate with the
same name/arity is translated a set of classes;there is one class for direct entry
point, and other classes for clauses. Each continuation goal is translated into a
term object, that is executed by referring to the hash table to transform it into
its corresponding predicate object.
Our example is first translated into the following binary clauses where Cont
represents a continuation goal:
p(Cont) :- q(r(Cont)).
q(Cont) :- call(Cont).
