Advances in learning classifier systems : 4th International Workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001 : revised papers
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Bibliographic Information
Advances in learning classifier systems : 4th International Workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001 : revised papers
（Lecture notes in computer science, 2321 . Lecture notes in artificial intelligence）
Springer, c2002
Available at 26 libraries
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Library, Research Institute for Mathematical Sciences, Kyoto University数研
L/N||LNCS||232102017744
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Includes bibliographical references and index
Description and Table of Contents
Description
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'?ciaAmancioVargas,ChristianoLyraFilho, FernandoJ. VonZuben VIII TableofContents CompactRulesetsfromXCSI ...197 StewartW. Wilson III Appendix AnAlgorithmicDescriptionofACS2 ...211 MartinV. Butz,WolfgangStolzmann AuthorIndex ...231 BiasingExplorationinan AnticipatoryLearningClassi?erSystem MartinV. Butz DepartmentofCognitivePsychology,UniversityofWurz .. burg R.. ontgenring11,97070Wurz .
. burg,Germany butz@psychologie. uni-wuerzburg. de Abstract. Thechapterinvestigateshowmodelandbehaviorallearning can be improved in an anticipatory learning classi?er system by bi- ing exploration. First, theappliedsystemACS2isexplained. Next,an overviewoverthepossibilitiesofapplyingexplorationbiasesinanant- ipatory learning classi?er systemand speci?cally ACS2 is provided.
Table of Contents
Theory.- Biasing Exploration in an Anticipatory Learning Classifier System.- An Incremental Multiplexer Problem and Its Uses in Classifier System Research.- A Minimal Model of Communication for a Multi-agent Classifier System.- A Representation for Accuracy-Based Assessment of Classifier System Prediction Performance.- A Self-Adaptive XCS.- Two Views of Classifier Systems.- Social Simulation Using a Multi-agent Model Based on Classifier Systems: The Emergence of Vacillating Behaviour in the "El Farol" Bar Problem.- Applications.- XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining.- A Preliminary Investigation of Modified XCS as a Generic Data Mining Tool.- Explorations in LCS Models of Stock Trading.- On-Line Approach for Loss Reduction in Electric Power Distribution Networks Using Learning Classifier Systems.- Compact Rulesets from XCSI.- An Algorithmic Description of ACS2.
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