000844085 000__ 05057cam\a2200577Ii\4500 000844085 001__ 844085 000844085 005__ 20230306144823.0 000844085 006__ m\\\\\o\\d\\\\\\\\ 000844085 007__ cr\cn\nnnunnun 000844085 008__ 180711s2018\\\\sz\\\\\\ob\\\\101\0\eng\d 000844085 019__ $$a1043849301 000844085 020__ $$a9783319905129$$q(electronic book) 000844085 020__ $$a3319905120$$q(electronic book) 000844085 020__ $$z9783319905112 000844085 020__ $$z3319905112 000844085 035__ $$aSP(OCoLC)on1043831050 000844085 035__ $$aSP(OCoLC)1043831050$$z(OCoLC)1043849301 000844085 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dGW5XE$$dEBLCP$$dYDX$$dOCLCF 000844085 049__ $$aISEA 000844085 050_4 $$aQA76.623 000844085 08204 $$a006.3/1$$223 000844085 1112_ $$aWorkshop on Genetic Programming, Theory and Practice$$n(15th :$$d2017 :$$cAnn Arbor, MI) 000844085 24510 $$aGenetic programming theory and practice XV /$$cWolfgang Banzhaf, Randal S. Olson, William Tozier, Rick Riolo, editors. 000844085 2463_ $$aGenetic programming theory and practice 15 000844085 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018] 000844085 264_4 $$c©2018 000844085 300__ $$a1 online resource. 000844085 336__ $$atext$$btxt$$2rdacontent 000844085 337__ $$acomputer$$bc$$2rdamedia 000844085 338__ $$aonline resource$$bcr$$2rdacarrier 000844085 4901_ $$aGenetic and evolutionary computation 000844085 504__ $$aIncludes bibliographical references and index. 000844085 5050_ $$aIntro; Foreword; Preface; Acknowledgements; Contents; Contributors; 1 Exploiting Subprograms in Genetic Programming; 1.1 Introduction; 1.2 Related Work; 1.3 Exploiting Subprograms; 1.3.1 BGP Strategy; 1.3.2 Exploring Model Bias; 1.3.3 Identifying Useful Subprograms; 1.4 Experiments; 1.4.1 Experimental Data, Parameters; 1.4.2 Sensitivity to Model Bias; 1.4.3 Aggregate Trace Matrices; 1.5 Conclusions and Future Work; References; 2 Schema Analysis in Tree-Based Genetic Programming; 2.1 Introduction; 2.1.1 Diversity and Evolutionary Dynamics; 2.1.2 Genetic Programming Schemata; 2.2 Methodology 000844085 5058_ $$a2.2.1 Schema Generation2.2.2 Schema Matching; 2.3 Experimental Setup; 2.3.1 Algorithm Parameters; 2.3.2 Problem Instances; 2.3.3 Analysis Methods; 2.4 Empirical Results; 2.4.1 Standard GP; Poly-10 Problem; Tower Problem; 2.4.2 Offspring Selection GP; Poly-10 Problem; 2.5 Conclusion; References; 3 Genetic Programming Symbolic Classification: A Study; 3.1 Introduction; 3.2 AMAXSC in Brief; 3.3 MDC in Brief; 3.4 M2GP in Brief; 3.5 LDA Background; 3.6 LDA Matrix Math; 3.7 LDA Assisted Fitness Implementation; 3.7.1 Converting to Basis Space; 3.7.2 Class Clusters and Centroids 000844085 5058_ $$a3.7.3 LDA Coefficients3.8 Artificial Test Problems; 3.9 Performance on Test Problems; 3.10 Conclusion; References; 4 Problem Driven Machine Learning by Co-evolving Genetic Programming Trees and Rules in a Learning Classifier System; 4.1 Introduction; 4.2 Methods; 4.2.1 ExSTraCS; 4.2.2 GP Integration; 4.2.2.1 GP Population Initialization; 4.2.2.2 GP Parent Selection; 4.2.2.3 GP Mating; 4.2.2.4 GP Fitness and Evaluation; 4.2.3 Datasets and Evaluation; 4.3 Preliminary Results; 4.4 Conclusions and Ongoing Work; References; 5 Applying Ecological Principles to Genetic Programming; 5.1 Introduction 000844085 5058_ $$a5.1.1 Motivation5.1.2 Ecological Approaches in Evolutionary Algorithms; 5.1.3 Limited Resources and Eco-EA; 5.1.4 Complexifying Environments; 5.2 Methods; 5.2.1 10-Dimensional Box Problem; 5.2.2 Eco-EA Implementation; 5.2.3 Lexicase Selection Implementation; 5.2.4 Tournament Selection Implementation; 5.2.5 Configuration Details; 5.2.6 Statistical Methods; 5.2.7 Code Availability; 5.3 Results and Discussion; 5.4 Conclusions and Future Work; References; 6 Lexicase Selection with Weighted Shuffle; 6.1 Introduction; 6.2 Lexicase Selection; 6.3 Weighted Shuffle; 6.3.1 Shuffling Methods 000844085 5058_ $$a6.3.2 Bias Metrics6.4 Experimental Setup; 6.4.1 Problems; 6.4.2 Push and PushGP; 6.5 Results; 6.6 Discussion; 6.7 Related Work; 6.8 Conclusions and Future Work; References; 7 Relaxations of Lexicase Parent Selection; 7.1 Introduction; 7.2 Lexicase Selection; 7.3 Epsilon Lexicase Selection; 7.4 Random Threshold Lexicase Selection; 7.5 MADCAP Epsilon Lexicase Selection; 7.6 Truncated Lexicase Selection; 7.7 Experimental Results; 7.8 Relation to Many-Objective Optimization; 7.9 Discussion; References; 8 A System for Accessible Artificial Intelligence; 8.1 Introduction; 8.2 The Human Engine 000844085 506__ $$aAccess limited to authorized users. 000844085 588__ $$aOnline resource; title from PDF title page (viewed July 13, 2018). 000844085 650_0 $$aGenetic programming (Computer science)$$vCongresses. 000844085 650_0 $$aArtificial intelligence$$vCongresses. 000844085 7001_ $$aBanzhaf, Wolfgang,$$d1955-$$eeditor. 000844085 7001_ $$aOlson, Randal S.,$$eeditor. 000844085 7001_ $$aTozier, William,$$eeditor. 000844085 7001_ $$aRiolo, Rick,$$eeditor. 000844085 77608 $$iPrint version: $$z3319905112$$z9783319905112$$w(OCoLC)1029798694 000844085 830_0 $$aGenetic and evolutionary computation series. 000844085 852__ $$bebk 000844085 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-90512-9$$zOnline Access$$91397441.1 000844085 909CO $$ooai:library.usi.edu:844085$$pGLOBAL_SET 000844085 980__ $$aEBOOK 000844085 980__ $$aBIB 000844085 982__ $$aEbook 000844085 983__ $$aOnline 000844085 994__ $$a92$$bISE