Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.
BuchGebunden
212 Seiten
Englisch
Springererschienen am12.02.20221st ed. 2022
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.mehr
Verfügbare Formate
BuchGebunden
EUR160,49
BuchKartoniert, Paperback
EUR160,49
E-BookPDF1 - PDF WatermarkE-Book
EUR149,79

Produkt

KlappentextThis 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.
Details
ISBN/GTIN978-981-16-8112-7
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2022
Erscheinungsdatum12.02.2022
Auflage1st ed. 2022
ReiheGenetic and Evolutionary Computation
Seiten212 Seiten
SpracheEnglisch
IllustrationenXIV, 212 p. 74 illus., 62 illus. in color.
Artikel-Nr.50263837

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1. Finding Simple Solutions to Multi-Task Visual Reinforcement Learning Problems with Tangled Program Graphs.- Chapter 2. Grammar-based Vectorial Genetic Programming for Symbolic Regression.- Chapter 3. Grammatical Evolution Mapping for Semantically-Constrained Genetic Programming.- Chapter 4. What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms?.- Chapter 5. An Exploration of Exploration: Measuring the ability of lexicaseselection to find obscure pathways to optimality.- Chapter 6. Feature Discovery with Deep Learning Algebra Networks.- Chapter 7. Back To The Future - Revisiting OrdinalGP & Trustable Models After a Decade.- Chapter 8. Fitness First.- Chapter 9. Designing Multiple ANNs with Evolutionary Development: Activity Dependence.- Chapter 10. Evolving and Analyzing modularity with GLEAM (Genetic Learning by Extraction and Absorption of Modules).- Chapter 11. Evolution of the Semiconductor Industry, and the Start of X Law.mehr

Autor