Transactions on Computational Collective Intelligence II PDF
Preview Transactions on Computational Collective Intelligence II
Lecture Notes in Computer Science 6450 CommencedPublicationin1973 FoundingandFormerSeriesEditors: GerhardGoos,JurisHartmanis,andJanvanLeeuwen EditorialBoard DavidHutchison LancasterUniversity,UK TakeoKanade CarnegieMellonUniversity,Pittsburgh,PA,USA JosefKittler UniversityofSurrey,Guildford,UK JonM.Kleinberg CornellUniversity,Ithaca,NY,USA AlfredKobsa UniversityofCalifornia,Irvine,CA,USA FriedemannMattern ETHZurich,Switzerland JohnC.Mitchell StanfordUniversity,CA,USA MoniNaor WeizmannInstituteofScience,Rehovot,Israel OscarNierstrasz UniversityofBern,Switzerland C.PanduRangan IndianInstituteofTechnology,Madras,India BernhardSteffen TUDortmundUniversity,Germany MadhuSudan MicrosoftResearch,Cambridge,MA,USA DemetriTerzopoulos UniversityofCalifornia,LosAngeles,CA,USA DougTygar UniversityofCalifornia,Berkeley,CA,USA GerhardWeikum MaxPlanckInstituteforInformatics,Saarbruecken,Germany Ngoc Thanh Nguyen Ryszard Kowalczyk (Eds.) Transactions on Computational Collective Intelligence II 1 3 VolumeEditors NgocThanhNguyen WroclawUniversityofTechnology InstituteofInformatics Str.Wyb.Wyspianskiego27 50-370Wroclaw,Poland E-mail:[email protected] RyszardKowalczyk SwinburneUniversityofTechnology CentreforComplexSoftwareSystemsandServices P.O.Box218 Hawthorn,Victoria3122,Australia E-mail:[email protected] LibraryofCongressControlNumber:Appliedfor CRSubjectClassification(1998):I.2,C.2.4,I.2.11,H.3-5,D.2 ISSN 0302-9743 ISBN-10 3-642-17154-0SpringerBerlinHeidelbergNewYork ISBN-13 978-3-642-17154-3SpringerBerlinHeidelbergNewYork Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerialis concerned,specificallytherightsoftranslation,reprinting,re-useofillustrations,recitation,broadcasting, reproductiononmicrofilmsorinanyotherway,andstorageindatabanks.Duplicationofthispublication orpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLawofSeptember9,1965, initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Violationsareliable toprosecutionundertheGermanCopyrightLaw. springer.com ©Springer-VerlagBerlinHeidelberg2010 PrintedinGermany Typesetting:Camera-readybyauthor,dataconversionbyScientificPublishingServices,Chennai,India Printedonacid-freepaper 06/3180 Preface Welcome to the second volume of Transactions on Computational Collective Intelli- gence (TCCI), a new journal devoted to research in computer-based methods of com- putational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intel- ligence technologies such as fuzzy systems, evolutionary computation, neural sys- tems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. TCCI is a double-blind refereed and authoritative reference dealing with the work- ing potential of CCI methodologies and applications, as well as emerging issues of interest to academics and practitioners. This second issue contains a collection of 10 articles selected from high-quality submissions addressing advances in the founda- tions and applications of computational collective intelligence. In “Integration Pro- posal for Description Logic and Attributive Logic – Towards Semantic Web Rules” G. Nalepa and W. Furmanska propose a transition from attributive logic to description logic in order to improve the design of Semantic Web rules. K. Thorisson et al. in “The Semantic Web: From Representation to Realization” present key ideas behind SemCard technology and its initial implementation, aiming to support management of the full lifecycle of data in the Semantic Web. “A Cross-cultural Multi-agent Model of Opportunism in Trade” by G. Hofstede et al. presents a model of deceit and trust in trade, together with a comparative multi-agent simulation of trading situations. L. Longo et al. in “Enhancing Social Search: A Computational Collective Intelligence Model of Behavioral Trait, Trust and Time” describe a social search model based on information foraging theory, effort and computational trust, showing a different way to implicitly judge Web-entities. “Group-Oriented Services: A Shift Toward Con- sumer-Managed Relationships in the Telecom Industry” by L. Vrdoljak et al. intro- duces an idea of a special type of personalized telecom services, called group-oriented services, and its application in agent-based mobile content brokerage. “Pricing the Services in Dynamic Environment: Agent Pricing Model” by D. Zagar et al. proposes an agent-based pricing architecture to enable objective and transparent assessment of the cost of the services. The next paper in this issue entitled “A Robust Approach for Nonlinear UAV Task Assignment Problem Under Uncertainty” by H.A. Le and Q.T. Nguyen includes a new robust approach to the task assignment of unmanned aerial vehicles operating in uncertain environments whose objective is maximizing the tar- get score. In “Decision Support System Based on Computational Collective Intelli- gence in Campus Information Systems” Y. Saito and T. Matsuo describe a method and an application of reusing campus collective information. “Fuel Crime Conceptu- alization Through Specialization of Ontology for Investigation Management System” by J. Cybulka presents a conceptual model based on consensual semantics to support VI Preface the teamwork of investigators of economics crimes. Finally, D. Barbucha et al. in “JABAT Middleware as a Tool for Solving Optimization Problems” present experi- ence in developing several applications of JABAT, a middleware supporting A-Team architecture for solving optimization problems. The research area of CCI has been growing significantly in recent years and we are very thankful to everyone within the CCI research community who has supported the Transactions on Computational Collective Intelligence and its affiliated events including the International Conferences on Computational Collective Intelligence: Semantic Web, Social Networks & Multiagent Systems (ICCCI). With this strong support and a large number of submissions we are very pleased that TCCI and ICCCI are being cemented as high-quality platforms for presenting and exchanging the most important and significant advances in CCI research and development. We would like to thank all the authors for their contributions to TCCI. This issue would also not have been possible without the great efforts of the editorial board and many anonymously acting reviewers. Here, we would like to express our sincere thanks to all of them. Finally, we would also like to express our gratitude to the LNCS editorial staff of Springer, in particular Alfred Hofmann, Ursula Barth and their team, who have supported the TCCI journal and the editorship of this issue in a very professional way. September 2010 Ngoc Thanh Nguyen Ryszard Kowalczyk Transactions on Computational Collective Intelligence This new journal focuses on research in applications of the computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. It aims to provide a forum for the presentation of scientific research and technological achievements accomplished by the international community. The topics addressed by this journal include all solutions of real-life problems for which it is necessary to use computational collective intelligence technologies to achieve effective results. The emphasis of the papers published is on novel and original research and technological advancements. Special features on specific topics are welcome. Editors-in-Chief Ngoc Thanh Nguyen Wroclaw University of Technology, Poland Ryszard Kowalczyk Swinburne University of Technology, Australia Editorial Board John Breslin National University of Ireland, Galway, Ireland Shi-Kuo Chang University of Pittsburgh, USA Oscar Cordon European Centre for Soft Computing, Spain Tzung-Pei Hong National University of Kaohsiung, Taiwan Gordan Jezic University of Zagreb, Croatia Piotr J(cid:266)drzejowicz Gdynia Maritime University, Poland Kang-Huyn Jo University of Ulsan, Korea Radosław Katarzyniak Wroclaw University of Technology, Poland Jozef Korbicz University of Zielona Gora, Poland Hoai An Le Thi Metz University, France Pierre Lévy University of Ottawa, Canada Tokuro Matsuo Yamagata University, Japan Kazumi Nakamatsu University of Hyogo, Japan Toyoaki Nishida Kyoto University, Japan Manuel Núñez Universidad Complutense de Madrid, Spain Julian Padget University of Bath, UK Witold Pedrycz University of Alberta, Canada Debbie Richards Macquarie University, Australia Roman Słowi(cid:276)ski Poznan University of Technology, Poland Edward Szczerbicki University of Newcastle, Australia Kristinn R. Thorisson Reykjavik University, Iceland Gloria Phillips-Wren Loyola University Maryland, USA Sławomir Zadro(cid:298)ny Institute of Research Systems, PAS, Poland Table of Contents Integration Proposal for Description Logic and Attributive Logic – Towards Semantic Web Rules............................... 1 Grzegorz J. Nalepa and Weronika T. Furman´ska A Cross-CulturalMulti-agent Model of Opportunism in Trade......... 24 Gert Jan Hofstede, Catholijn M. Jonker, and Tim Verwaart Enhancing Social Search: A Computational Collective Intelligence Model of BehaviouralTraits, Trust and Time........................ 46 Luca Longo, Pierpaolo Dondio, and Stephen Barrett Group-Oriented Services: A Shift towards Consumer-Managed Relationships in the Telecom Industry .............................. 70 Luka Vrdoljak, Iva Bojic, Vedran Podobnik, Gordan Jezic, and Mario Kusek The Semantic Web: From Representation to Realization .............. 90 Kristinn R. Tho´risson, Nova Spivack, and James M. Wissner Decision Support System Based on Computational Collective Intelligence in Campus Information Systems......................... 108 Yoshihito Saito and Tokuro Matsuo Fuel Crime Conceptualization through Specialization of Ontology for Investigation Management System ................................. 123 Jolanta Cybulka A Robust Approach for Nonlinear UAV Task Assignment Problem under Uncertainty ............................................... 147 Le Thi Hoai An and Nguyen Quang Thuan Pricing the Services in Dynamic Environment: Agent Pricing Model .... 160 Drago Zˇagar, Slavko Rupˇci´c, and Snjeˇzana Rimac-Drlje JABAT Middleware as a Tool for Solving Optimization Problems ...... 181 Dariusz Barbucha, Ireneusz Czarnowski, Piotr Je¸drzejowicz, Ewa Ratajczak-Ropel, and Izabela Wierzbowska Author Index.................................................. 197 Integration Proposal for Description Logic and (cid:2) Attributive Logic – Towards Semantic Web Rules Grzegorz J. Nalepa and Weronika T. Furmańska Instituteof Automatics, AGHUniversity of Science and Technology, Al. Mickiewicza 30, 30-059 Kraków, Poland [email protected], [email protected] Abstract. The current challenge of the Semantic Web is the develop- mentofanexpressiveyeteffectiverulelanguage.Thispaperpresentsan integration proposal for Description Logics (DL)and AttributiveLogics (ALSV) is presented. These two formalisms stem from fields of Knowl- edgeRepresentationandArtificialIntelligence.However,theyarebased on different design goals and therefore provide different description and reasoning capabilities. ALSV is the foundation of XTT2, an expressive language for rule-based systems. DL provide formulation for expressive ontology languages such as OWL2. An important research direction is thedevelopmentofrulelanguagesthatcanbeintegratedwithontologies. The contribution of the paper consists in introducing a possible transi- tion from ALSV to DL. This opens up possibilities of using XTT2, a well-founded rule-based system modelling rule language, to improvethe design of SemanticWeb rules1. 1 Introduction The Semantic Webproposal[2],ofthe next generationWeb withrichsemantics and automated inference is based on a number of formalconcepts and practical technologies. The former includes Description Logics (DL) [3] as the formalism fordescribingontologies.Currently,theSemanticWebdevelopmentisfocusedon providingaflexiblerulelanguagefortheWeb.ItshouldbeRIF-compatible[4]on theruleinterchangelevel,andconceptuallycompatiblewithontologiesmodelled in OWL with the use of Description Logics.Among other proposals,the SWRL language [5] aims at meeting these requirements. The Semantic Web initiativeis basedonpreviousexperiencesandresearchof Knowledge Engineering [6] in the field of Artificial Intelligence [7]. In this field rule-basedexpertsystemstechnologiesareaprimeexampleofeffectivereasoning systems based on the rule paradigm [8,9,10]. The formal description of these (cid:2) The paper is supported by the BIMLOQ Project funded from 2010–2012 resources for science as a research project. 1 The paper extends concepts and preliminary results described in the paper [1] pre- sented at ICCCI’09 Conference in Wrocław, Poland. N.T.NguyenandR.Kowalczyk(Eds.):TransactionsonCCIII,LNCS6450,pp.1–23,2010. (cid:2)c Springer-VerlagBerlinHeidelberg2010 2 G.J. Nalepa and W.T. Furmańska systems is based on the propositional calculus, or restricted form of predicate logic – like in the case of Prolog [11]. It is worth noting how the Semantic Web community could benefit from classic rule-based systems’ tools and solutions. A recent proposal of a new logical calculus extends the expressiveness of rulelanguagesbyintroducinganattributivelanguageforruleformulation[10,12]. This solution seems superior to the simple propositional systems, and still easier to reasonwith than the classicalpredicate logic.XTT2 is a rule language based on this approach [12,13]. It provides visual design and formal analysis methodsfordecisionrules.Thesefeatureswouldbe beneficialforSemanticWeb applications.However,thecurrentproblemwithAttributiveLogicwithSetVal- uesoverFiniteDomain(ALSV(FD))isthelackofconceptualcompatibilitywith DL. The rest of this paper is organised as follows: selected DL concepts are discussed in Sect. 2, and a brief introduction to ALSV(FD) is given in Sect. 3. Sect. 4 givesa motivationfor the researchaiming attranslationfromthe ALSV (FD) to DL. ALSV(FD) is oriented at forward chaining rule-based systems, while DL providesa formalizedfoundationfor ontologies.Syntaxand semantics of these two calculi are compared in Sect. 5. In Sect. 6 an integration proposal togetherwith a descriptionlanguageis introduced.A simple example transition is then presented in Sect. 7. In Sect. 8 the proposal is evaluated and compared with selected existing solutions in Sect. 9. The paper ends with ideas for future work. 2 Description Logics Overview DescriptionLogicsareafamilyofknowledgerepresentationlanguages[3].Histor- icallyrelatedtosemanticnetworksandframelanguages,theydescribetheworld ofinterestbymeansofconcepts,individualsandroles.However,contrarytotheir predecessors such as semantic networks [6], they provide formal semantics and thus allow for automated reasoning.Basic Description Logics take advantage of theirrelationtopredicatecalculus.Ononehandtheyadoptitssemantics,which makesthemmoreexpressivethanthepropositionallogic.Ontheotherhand,by restricting the syntax to formulae with at most two variables, they remain de- cidableandmorehuman-readable.ThesefeatureshavemadeDescriptionLogics a popular formalism used for designing ontologies for the Semantic Web. There exists a number of DL languages that are defined and distinguished by which concept descriptions they allow, which influences the languages’ expressivity. The vocabulary in DL consists of languages are concepts, which denote sets ofindividuals, and roles, whichdenote the binaryrelations betweenindividuals. ElementarydescriptionsinDLareatomic concepts andatomic roles.Morecom- plexdescriptionscanbe builtinductivelyfromthoseusingconcept constructors. Respective DL languages are distinguished by the constructors they provide. A minimal language of practical interest is the Attributive Language [3] (AL). Integration Proposal for Description Logic 3 Some of the most important definitions are presented (see [3]) below. Definition 1. Let A denote an atomic concept and R an atomic role. In basic AL concept descriptions C and D can be in one of the following forms: A atomic concept (1) (cid:2) universal concept (2) ⊥ bottom concept (3) ¬A atomic negation (4) C(cid:4)D intersection (5) ∀R.C value restriction (6) ∃R.(cid:2) limited existential quantification (7) In order to define a formal semantics, an interpretation I = (ΔI,·I) is con- sidered. This interpretation consists of the domain of interpretation which is a non-empty set and an interpretation function, which to every atomic con- cept A assigns a set AI ⊆ ΔI and for every atomic role R a binary relation RI = RI ⊆ ΔI × ΔI. The interpretation function is extended over concept descriptions by Definition 2. Definition 2. (cid:2)I =ΔI (8) ⊥I =∅ (9) (¬A)I =ΔI \AI (10) (C(cid:4)D)I =CI ∩DI (11) (∀R.C)I ={a∈ΔI|∀b,(a,b)∈RI →b∈CI} (12) (∃R.(cid:2))I ={a∈ΔI|∃b,(a,b)∈RI} (13) Thebasiclanguagecanbeextendedbyallowingotherconceptconstructors,such as union (U) , full negation (C), full existential quantification (E) or number restriction (N). Resulting formalisms are called using the letters indicating the allowedconstructors,e.g.ALC,ALCN,ALUE etc.Thesmallestpropositionally closed language is ALC [3]. Basic DL allowonly atomic roles (i.e. rolenames) in roledescriptions.Differ- ent extensions are introduced by allowing role constructors. They enable intro- duction of various constraints and properties of roles,such as transitive closure, intersection, composition and union, or complement and inverse roles. Another kind of extension is obtained by allowing nominals in concept definitions and introducing primitive datatypes (see [3]). These modifications proved to be ex- tremelyvaluableandimportantinthecontextoftheSemanticWebandontology engineering.However,they aresourcesofhighcomputationalcomplexityofrea- soning in the resulting ontologies.
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