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´?ciaAmËancioVargas, 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. | Advances in Learning Classifier Systems by Pier L. Lanzi, Paperback | Indigo Chapters