Genetic Programming
23rd European Conference, EuroGP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15-17, 2020, Proceedings
(Sprache: Englisch)
This book constitutes the refereed proceedings of the 23rd European Conference on Genetic Programming, EuroGP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EvoCOP, EvoMUSART and EvoApplications.
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Klappentext zu „Genetic Programming “
This book constitutes the refereed proceedings of the 23rd European Conference on Genetic Programming, EuroGP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EvoCOP, EvoMUSART and EvoApplications.The 12 full papers and 6 short papers presented in this book were carefully reviewed and selected from 36 submissions. The papers cover a wide spectrum of topics, including designing GP algorithms for ensemble learning, comparing GP with popular machine learning algorithms, customising GP algorithms for more explainable AI applications to real-world problems.
Inhaltsverzeichnis zu „Genetic Programming “
Hessian Complexity Measure for Genetic Programming-based Imputation Predictor Selection in Symbolic Regression with Incomplete Data.- Seeding Grammars in Grammatical Evolution to Improve Search Based Software Testing.- Incremental Evolution and Development of Deep Artificial Neural Networks.- Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming.- Comparing Genetic Programming Approaches for Non-Functional Genetic Improvement.- Automatically Evolving Lookup Tables for Function Approximation.- Optimising Optimisers with Push GP.- An Evolutionary View on Reversible Shift-invariant Transformations.- Benchmarking Manifold Learning Methods on a Large Collection of Datasets.- Ensemble Genetic Programming.- SGP-DT: Semantic Genetic Programming Based on Dynamic Targets.- Effect of Parent Selection Methods on Modularity.- Time Control or Size Control? Reducing Complexity and Improving Accuracy of Genetic Programming Models.- Challenges of Program Synthesis withGrammatical Evolution.- Detection of Frailty Using Genetic Programming : The Case of Older People in Piedmont, Italy.- Is k Nearest Neighbours Regression Better than GP.- Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling.- Classification of Autism Genes using Network Science and Linear Genetic Programming.
Bibliographische Angaben
- 2020, 1st ed. 2020, X, 295 Seiten, 72 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Ting Hu, Nuno Lourenço, Eric Medvet, Federico Divina
- Verlag: Springer, Berlin
- ISBN-10: 3030440931
- ISBN-13: 9783030440930
Sprache:
Englisch
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