advances learning classifier systems (34 resultados)

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Paperback. Condición: new. Paperback. This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001, held in San Francisco, CA, USA, in July 2001. The 12 revised full papers presented together with a special paper on a formal description of ACS have gone through two rounds of reviewing and improvement. The first part of the book is devoted to theoretical issues of learning classifier systems including the influence of exploration strategy, self-adaptive classifier systems, and the use of classifier systems for social simulation. The second part is devoted to applications in various fields such as data mining, stock trading, and power distributionn networks. These are the refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001. The first part is devoted to theoretical issues, and the second to applications in various fields such as data mining, stock trading, and power distribution networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Paperback. Condición: new. Paperback. This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Learning Classifier Systems, IWLCS 2000, held in Paris, France in September 2000. The 13 revised full papers presented have gone through two rounds of reviewing and selection. Also included is a comprehensive LCS bibliography listing more than 600 entries as well as an appendix. The papers are organized in topical sections on theory, applications, and advanced architectures. Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condición: New. pp. 288.

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Condición: New. Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been ap.

Taschenbuch. Condición: Neu. Neuware -UniversityofPennsylvania,USA TimKovacs UniversityofBirmingham,UK PierLucaLanzi PolitecnicodiMilano,Italy RickL. Riolo UniversityofMichigan,USA OlivierSigaud AnimatLab-LIP6,France RobertE. Smith TheUniversityofTheWestofEngland,UK WolfgangStolzmann DaimlerChryslerAG,Germany KeikiTakadama ATRInternational,Japan StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA TableofContents ITheory BiasingExplorationinanAnticipatoryLearningClassi erSystem . . . . . . . 3 MartinV. Butz An Incremental Multiplexer Problem and Its Uses in Classi er System Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 LawrenceDavis,ChunshengFu,StewartW. Wilson AMinimalModelofCommunicationforaMulti-agentClassi erSystem. . 32 ¿ GillesEn¿ee,CathyEscazut A Representation for Accuracy-Based Assessment of Classi er System PredictionPerformance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 JohnH. Holmes ASelf-AdaptiveXCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 JacobHurst,LarryBull TwoViewsofClassi erSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 TimKovacs SocialSimulationUsingaMulti-agentModelBasedonClassi erSystems: TheEmergenceofVacillatingBehaviourinthe¿ElFarol¿BarProblem. . . 88 LuisMiramontesHercog,TerenceC. Fogarty II Applications XCSandGALE:AComparativeStudyofTwoLearningClassi erSystems onDataMining. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 EsterBernad¿o,XavierLlor`a,JosepM. Garrell APreliminaryInvestigationofModi edXCSasaGenericDataMining Tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 PhillipWilliamDixon,DavidW. Corne,MartinJohnOates ExplorationsinLCSModelsofStockTrading . . . . . . . . . . . . . .Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been applied to domains as diverse as autonomous robotics, trading agents, and data mining. At the Second International Workshop on Learning Classi er Systems (IWLCS 99), held July 13, 1999, in Orlando, Florida, active researchers reported on the then current state of learning classi er system research and highlighted some of the most promising research directions. The most interesting contri- tions to the meeting are included in the book Learning Classi er Systems: From Foundations to Applications, published as LNAI 1813 by Springer-Verlag. The following year, the Third International Workshop on Learning Classi er Systems (IWLCS 2000), held September 15{16 in Paris, gave participants the opportunity to discuss further advances in learning classi er systems. We have included in this volume revised and extended versions of thirteen of the papers presented at the workshop.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The Fourth International Workshop on Learning Classi er Systems (IWLCS 2001)washeldJuly7-8,2001,inSanFrancisco,California,duringtheGenetic andEvolutionaryComputationConference(GECCO2001). Wehaveincluded inthisvolumerevisedandextendedversionsofelevenofthepaperspresented attheworkshop. Thevolumeisorganizedintotwomainparts. The rstisdedicatedtoimportant theoreticalissuesoflearningclassi ersystemsresearchincludingthein uence ofexplorationstrategy,amodelofself-adaptiveclassi ersystems,andtheuse ofclassi ersystemsforsocialsimulation. Thesecondpartcontainspapersd- cussing applications of learning classi er systems such as data mining, stock trading,andpowerdistributionnetworks. AnappendixcontainsapaperpresentingaformaldescriptionofACS,arapidly emerginglearningclassi ersystemmodel. Thisbookistheidealcontinuationofthetwovolumesfromthepreviouswo - shops,publishedbySpringer-VerlagasLNAI1813andLNAI1996. Wehopeit willbeausefulsupportforresearchersinterestedinlearningclassi ersystems andwillprovideinsightsintothemostrelevanttopicsandthemostinteresting openissues. April2002 PierLucaLanzi WolfgangStolzmann StewartW. Wilson Organization The Fourth International Workshop on Learning Classi er Systems (IWLCS 2001)washeldJuly7-8,2001inSanFrancisco(CA),USA,duringtheGenetic andEvolutionaryConference(GECCO2001). OrganizingCommittee PierLucaLanzi PolitecnicodiMilano,Italy WolfgangStolzmann DaimlerChryslerAG,Germany StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA ProgramCommittee ErikBaum NECResearchInstitute,USA AndreaBonarini PolitecnicodiMilano,Italy LashonB. Booker TheMITRECorporation,USA MartinV. Butz UniversityofWur zburg,Germany LawrenceDavis NuTechSolutions,USA TerryFogarty SouthbankUniversity,UK JohnH. Holmes UniversityofPennsylvania,USA TimKovacs UniversityofBirmingham,UK PierLucaLanzi PolitecnicodiMilano,Italy RickL. Riolo UniversityofMichigan,USA OlivierSigaud AnimatLab-LIP6,France RobertE. Smith TheUniversityofTheWestofEngland,UK WolfgangStolzmann DaimlerChryslerAG,Germany KeikiTakadama ATRInternational,Japan StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA TableofContents ITheory BiasingExplorationinanAnticipatoryLearningClassi erSystem . . . . . . . 3 MartinV. Butz An Incremental Multiplexer Problem and Its Uses in Classi er System Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 LawrenceDavis,ChunshengFu,StewartW. Wilson AMinimalModelofCommunicationforaMulti-agentClassi erSystem. . 32 GillesEn ee,CathyEscazut A Representation for Accuracy-Based Assessment of Classi er System PredictionPerformance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 JohnH. Holmes ASelf-AdaptiveXCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 JacobHurst,LarryBull TwoViewsofClassi erSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 TimKovacs SocialSimulationUsingaMulti-agentModelBasedonClassi erSystems: TheEmergenceofVacillatingBehaviourinthe ElFarol BarProblem. . . 88 LuisMiramontesHercog,TerenceC. Fogarty II Applications XCSandGALE:AComparativeStudyofTwoLearningClassi erSystems onDataMining. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 EsterBernad o,XavierLlor`a,JosepM. Garrell APreliminaryInvestigationofModi edXCSasaGenericDataMining Tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 PhillipWilliamDixon,DavidW. Corne,MartinJohnOates ExplorationsinLCSModelsofStockTrading . . . . . . . . . . . . . . . . . . . . . . . . . 151 SoniaSchulenburg,PeterRoss On-LineApproachforLossReductioninElectricPowerDistribution NetworksUsingLearningClassi erSystems. . . . . . . . . . . . . . . . . . . . . . .

Paperback. Condición: new. Paperback. This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001, held in San Francisco, CA, USA, in July 2001. The 12 revised full papers presented together with a special paper on a formal description of ACS have gone through two rounds of reviewing and improvement. The first part of the book is devoted to theoretical issues of learning classifier systems including the influence of exploration strategy, self-adaptive classifier systems, and the use of classifier systems for social simulation. The second part is devoted to applications in various fields such as data mining, stock trading, and power distributionn networks. These are the refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001. The first part is devoted to theoretical issues, and the second to applications in various fields such as data mining, stock trading, and power distribution networks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condición: New. pp. 244.

Paperback. Condición: new. Paperback. This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Learning Classifier Systems, IWLCS 2000, held in Paris, France in September 2000. The 13 revised full papers presented have gone through two rounds of reviewing and selection. Also included is a comprehensive LCS bibliography listing more than 600 entries as well as an appendix. The papers are organized in topical sections on theory, applications, and advanced architectures. Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condición: New.

Taschenbuch oder Softcover. Condición: Sehr gut. Zustand: SEHR GUTER Zustand! Stichworte: Lernendes System, Automatische Klassifikation, Kongress, San Francisco , Konferenzschrift Englisch 380g.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Fourth International Workshop on Learning Classi er Systems (IWLCS 2001)washeldJuly7-8,2001,inSanFrancisco,California,duringtheGenetic andEvolutionaryComputationConference(GECCO2001). Wehaveincluded inthisvolumerevisedandextendedversionsofelevenofthepaperspresented attheworkshop. Thevolumeisorganizedintotwomainparts. The rstisdedicatedtoimportant theoreticalissuesoflearningclassi ersystemsresearchincludingthein uence ofexplorationstrategy,amodelofself-adaptiveclassi ersystems,andtheuse ofclassi ersystemsforsocialsimulation. Thesecondpartcontainspapersd- cussing applications of learning classi er systems such as data mining, stock trading,andpowerdistributionnetworks. AnappendixcontainsapaperpresentingaformaldescriptionofACS,arapidly emerginglearningclassi ersystemmodel. Thisbookistheidealcontinuationofthetwovolumesfromthepreviouswo- shops,publishedbySpringer-VerlagasLNAI1813andLNAI1996. Wehopeit willbeausefulsupportforresearchersinterestedinlearningclassi ersystems andwillprovideinsightsintothemostrelevanttopicsandthemostinteresting openissues. April2002 PierLucaLanzi WolfgangStolzmann StewartW. Wilson Organization The Fourth International Workshop on Learning Classi er Systems (IWLCS 2001)washeldJuly7-8,2001inSanFrancisco(CA),USA,duringtheGenetic andEvolutionaryConference(GECCO2001). OrganizingCommittee PierLucaLanzi PolitecnicodiMilano,Italy WolfgangStolzmann DaimlerChryslerAG,Germany StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA ProgramCommittee ErikBaum NECResearchInstitute,USA AndreaBonarini PolitecnicodiMilano,Italy LashonB. Booker TheMITRECorporation,USA MartinV. Butz UniversityofWur zburg,Germany LawrenceDavis NuTechSolutions,USA TerryFogarty SouthbankUniversity,UK JohnH. Holmes UniversityofPennsylvania,USA TimKovacs UniversityofBirmingham,UK PierLucaLanzi PolitecnicodiMilano,Italy RickL. Riolo UniversityofMichigan,USA OlivierSigaud AnimatLab-LIP6,France RobertE. Smith TheUniversityofTheWestofEngland,UK WolfgangStolzmann DaimlerChryslerAG,Germany KeikiTakadama ATRInternational,Japan StewartW. Wilson TheUniversityofIllinoisatUrbana-Champaign,USA PredictionDynamics,USA TableofContents ITheory BiasingExplorationinanAnticipatoryLearningClassi erSystem . . . . . . . 3 MartinV. Butz An Incremental Multiplexer Problem and Its Uses in Classi er System Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 LawrenceDavis,ChunshengFu,StewartW. Wilson AMinimalModelofCommunicationforaMulti-agentClassi erSystem. . 32 GillesEn ee,CathyEscazut A Representation for Accuracy-Based Assessment of Classi er System PredictionPerformance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 JohnH. Holmes ASelf-AdaptiveXCS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 JacobHurst,LarryBull TwoViewsofClassi erSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 TimKovacs SocialSimulationUsingaMulti-agentModelBasedonClassi erSystems: TheEmergenceofVacillatingBehaviourinthe ElFarol BarProblem. . . 88 LuisMiramontesHercog,TerenceC. Fogarty II Applications XCSandGALE:AComparativeStudyofTwoLearningClassi erSystems onDataMining. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 EsterBernad o,XavierLlor`a,JosepM. Garrell APreliminaryInvestigationofModi edXCSasaGenericDataMining Tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 PhillipWilliamDixon,DavidW. Corne,MartinJohnOates ExplorationsinLCSModelsofStockTrading . . . . . . . . . . . . . . . . . . . . . . . . . 151 SoniaSchulenburg,PeterRoss On-LineApproachforLossReductioninElectricPowerDistribution NetworksUsingLearningClassi erSystems. . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Patr ciaAm ancioVargas,ChristianoLyr 244 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Learning classi er systems are rule-based systems that exploit evolutionary c- putation and reinforcement learning to solve di cult problems. They were - troduced in 1978 by John H. Holland, the father of genetic algorithms, and since then they have been applied to domains as diverse as autonomous robotics, trading agents, and data mining. At the Second International Workshop on Learning Classi er Systems (IWLCS 99), held July 13, 1999, in Orlando, Florida, active researchers reported on the then current state of learning classi er system research and highlighted some of the most promising research directions. The most interesting contri- tions to the meeting are included in the book Learning Classi er Systems: From Foundations to Applications, published as LNAI 1813 by Springer-Verlag. The following year, the Third International Workshop on Learning Classi er Systems (IWLCS 2000), held September 15{16 in Paris, gave participants the opportunity to discuss further advances in learning classi er systems. We have included in this volume revised and extended versions of thirteen of the papers presented at the workshop. 288 pp. Englisch.

Condición: New. Print on Demand pp. 288 Illus.