Genetic programming : 22nd European Conference, EuroGP 2019, held as part of EvoStar 2019, Leipzig, Germany, April 24-26, 2019, Proceedings / Lukas Sekanina, Ting Hu, Nuno Lourenço, Hendrik Richter, Pablo García-Sánchez (eds.).
EuroGP (Conference) (22nd : 2019 : Leipzig, Germany); Sekanina, Lukáš, editor.; Hu, Ting, editor.; Lourenço, Nuno, editor.; Richter, Hendrik, editor.; García-Sánchez , Pablo, editor.; EVOSTAR (Conference) (2019 : Leipzig, Germany)
2019
QA76.623
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Title Genetic programming : 22nd European Conference, EuroGP 2019, held as part of EvoStar 2019, Leipzig, Germany, April 24-26, 2019, Proceedings / Lukas Sekanina, Ting Hu, Nuno Lourenço, Hendrik Richter, Pablo García-Sánchez (eds.).
Meeting Name EuroGP (Conference) (22nd : 2019 : Leipzig, Germany)
ISBN 9783030166700 (electronic book)
3030166708 (electronic book)
9783030166694
DOI https://doi.org/10.1007/978-3-030-16670-0
Published Cham, Switzerland : Springer, 2019.
Language English
Description 1 online resource (xii, 295 pages) : illustrations.
Item Number 10.1007/978-3-030-16670-0 doi
Call Number QA76.623
Dewey Decimal Classification 006.3/823
Summary This book constitutes the refereed proceedings of the 22nd European Conference on Genetic Programming, EuroGP 2019, held as part of Evo* 2019, in Leipzig, Germany, in April 2019, co-located with the Evo* events EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 6 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They cover a wide range of topics and reflect the current state of research in the field. With a special focus on real-world applications in 2019, the papers are devoted to topics such as the test data design in software engineering, fault detection and classification of induction motors, digital circuit design, mosquito abundance prediction, machine learning and cryptographic function design.
Note International conference proceedings.
Includes author index.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 22, 2019).
Added Author Sekanina, Lukáš, editor.
Hu, Ting, editor.
Lourenço, Nuno, editor.
Richter, Hendrik, editor.
García-Sánchez , Pablo, editor.
Added Meeting Name EVOSTAR (Conference) (2019 : Leipzig, Germany)
Series Lecture notes in computer science ; 11451.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
Available in Other Form Print version: 9783030166694
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[I]. Long presentations: 1. Ariadne : evolving test data using grammatical evolution / Muhammad Sheraz Anjum, Conor Ryan
2. Quantum program synthesis : swarm algorithms and benchmarks / Timothy Atkinson, Athena Karsa, John Drake, Jerry Swan
3. A genetic programming approach to predict mosquitoes abundance / Riccardo Gervasi, Irene Azzali, Donal Bisanzio, Andrea Mosca, Luigi Bertolotti, Mario Giacobini
4. Complex network analysis of a genetic programming phenotype network / Ting Hu, Marco Tomassini, Wolfgang Banzhof
5. Improving genetic programming with novel exploration : exploitation control / Jonathan Kelly, Erik Hemberg, Una-May O'Reilly
6. Towards a scalable EA-based optimization of digital circuits / Jitka Kocnova, Zdenek Vasicek
7. Cartesian genetic programming as an optimizer of programs evolved with geometric semantic genetic programming / Ondrej Koncal, Lukas Sekanina
8. Can genetic programming do manifold learning too? / Andrew Lensen, Bing Xue, Mengjie Zhang
9. Why is auto-encoding difficult for genetic programming? / James McDermott
10. Solution and fitness evolution (SAFE) : coevolving solutions and their objective functions / Moshe Sipper, James H. Moore, Ryan J. Urbanowicz
11. A model of external memory for navigation in partially observable visual reinforcement learning tasks / Robert J. Smith, Malcolm I. Heywood
12. Fault detection and classification for induction motors using genetic programming / Yu Zhang, Ting Hu, Xiaodong Liang, Mohammad Zawad Ali, Md. Nasmus Sakib Khan Shabbir.

[II]. Short presentations: 13. Fast DENSER : efficient deep NeuroEvolution / Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro
14. A vectorial approach to genetic programming / Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini
15. Comparison of genetic programming methods on design of cryptographic Boolean functions / Jakub Husa
16. Evolving AVX512 parallel C code using GP / William B. Langdon, Ronny Lorenz
17. Hyper-bent Boolean functions and evolutionary algorithms / Luca Mariot, Domagoj Jakobovic, Alberto Leporati, Stjepan Picek
18. Learning class disjointness axioms using grammatical evolution / Thu Huong Nguyen, Andrea G.B. Tettamanzi.

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