<p><span>Genetic Programming Theory and Practice brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning
Genetic Programming Theory and Practice XX (Genetic and Evolutionary Computation)
β Scribed by Stephan Winkler (editor), Leonardo Trujillo (editor), Charles Ofria (editor), Ting Hu (editor)
- Publisher
- Springer
- Year
- 2024
- Tongue
- English
- Leaves
- 352
- Edition
- 1st ed. 2024
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Genetic Programming Theory and Practice brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this yearβs book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine, and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the- art in GP research.
π SIMILAR VOLUMES
<span>This book, written by the foremost international researchers and practitioners of genetic programming (GP), explores the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. In this yearβs edition, the topics co
<p></p><p><span>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. In this yearβs edi
In comparing this book with, say Goldberg's "Genetic Algorithms..." (may be the most popular genetic algorithms text), this book reads more like a German habilitation thesis (which I imagine it may have served as such), where as Goldberg's book seems more of a light introduction for the mathematical