Genetic Programming Theory and Practice XIV, Softcover reprint of the original 1st ed. 2018 Genetic and Evolutionary Computation Series
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.
Provides chapters describing cutting-edge work on the theory and applications of genetic programming (GP)
Offers large-scale, real-world applications of GP to a variety of problem domains
Written by leading international experts from both academia and industry
Date de parution : 01-2019
Ouvrage de 227 p.
15.5x23.5 cm
Date de parution : 11-2018
Ouvrage de 227 p.
15.5x23.5 cm
Thème de Genetic Programming Theory and Practice XIV :
Mots-clés :
Genetic programming; Genetic programming theory; Genetic programming applications; Symbolic regression; Evolution of models; Program induction; Artificial evolution; Feature selection; Artificial General Intelligence; Distributed Probabilistic Rule; Dispersion Operators; Evolutionary Augmentation; Analogical Reasoning; algorithm analysis and problem complexity