E-Book, Englisch, 212 Seiten, eBook
E-Book, Englisch, 212 Seiten, eBook
Reihe: Genetic and Evolutionary Computation
ISBN: 978-981-16-8113-4
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.