| Description |
1 online resource (x, 295 pages) : illustrations (some color) |
| Series |
Lecture notes in computer science ; 12101 |
|
LNCS sublibrary. SL 1, Theoretical computer science and general issues |
|
Lecture notes in computer science ; 12101.
|
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LNCS sublibrary. SL 1, Theoretical computer science and general issues.
|
| Contents |
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 with Grammatical 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 |
| Summary |
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 |
| Notes |
International conference proceedings |
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Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed April 20, 2020) |
| Subject |
Genetic programming (Computer science) -- Congresses
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|
Genetic programming (Computer science)
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
|
| Author |
Hu, Ting (Assistant professor of computer science), editor.
|
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Lourenço, Nuno, editor
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Medvet, Eric, editor
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Divina, Federico, editor
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EVOSTAR (Conference) (2020 : Seville, Spain), jointly held conference.
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| ISBN |
9783030440947 |
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303044094X |
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3030440931 |
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9783030440930 |
|
9783030440954 |
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3030440958 |
|
