Genetic Programming Theory and Practice XIV (eBook)

Rick Riolo, Bill Worzel, Brian Goldman, Bill Tozier (Herausgeber)

eBook Download: PDF

2018 | 1st ed. 2018
XV, 227 Seiten
Springer International Publishing (Verlag)
978-3-319-97088-2 (ISBN)

Infos

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Chapters in this volume include: 

• Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression
  
• Hybrid Structural and Behavioral Diversity Methods in GP
  
• Multi-Population Competitive Coevolution for Anticipation of Tax Evasion
  
• Evolving Artificial General Intelligence for Video Game Controllers
  
• A Detailed Analysis of a PushGP Run
  
• Linear Genomes for Structured Programs
  
• Neutrality, Robustness, and Evolvability in GP
  
• Local Search in GP
  
• PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification
  
• Relational Structure in Program Synthesis Problems with Analogical Reasoning
  
• An Evolutionary Algorithm for Big Data Multi-Class Classification Problems
  
• A Generic Framework for Building Dispersion Operators in the Semantic Space
  
• Assisting Asset Model Development with Evolutionary Augmentation
  
• Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool 

Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

Inhalt

1 Similarity-based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression.- 2 An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming.- 3 Investigating Multi-Population Competitive Coevolution for Anticipation of Tax Evasion.- 4 Evolving Artificial General Intelligence for Video Game Controllers.- 5 A Detailed Analysis of a PushGP Run.- 6 Linear Genomes for Structured Programs.- 7 Neutrality, Robustness, and Evolvability in Genetic Programming.- 8 Local Search is Underused in Genetic Programming.- 9 PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification.- 10 Discovering Relational Structural in Program Synthesis Problems with Analogical Reasoning.- 11 An Evolutionary Algorithm for Big Data Multi-Class Classification Problems.- 12 A Genetic Framework for Building Dispersion Operators in the Semantic Space.- 13 Assisting Asset Model Development with Evolutionary Augmentation.- 14 Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool.

Produkt-Details

• Erscheint lt. Verlag: 24.10.2018
• Reihe/Serie: Genetic and Evolutionary Computation
• Reihe/Serie: Genetic and Evolutionary Computation
• Zusatzinfo: XV, 227 p. 52 illus.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: Algorithm analysis and problem complexity • Analogical Reasoning • Artificial Evolution • artificial general intelligence • Dispersion Operators • Distributed Probabilistic Rule • Evolutionary Augmentation • Evolution of Models • Feature Selection • genetic programming • Genetic Programming Applications • Genetic Programming Theory • program induction • Symbolic Regression
• ISBN-10: 3-319-97088-7 / 3319970887
• ISBN-13: 978-3-319-97088-2 / 9783319970882