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Genetic Programming : 23rd European Conference, EuroGP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15-17, 2020, Proceedings / edited by Ting Hu, Nuno Lourenço, Eric Medvet, Federico Divina.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Theoretical computer science and general issues 2512-2029 ; SL 1, 12101
- Theoretical Computer Science and General Issues, 2512-2029 ; 12101
- Language:
- English
- Subjects (All):
- Computer science.
- Computer systems.
- Computers, Special purpose.
- Computer networks.
- Artificial intelligence.
- Computer engineering.
- Theory of Computation.
- Computer System Implementation.
- Special Purpose and Application-Based Systems.
- Computer Communication Networks.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Local Subjects:
- Theory of Computation.
- Computer System Implementation.
- Special Purpose and Application-Based Systems.
- Computer Communication Networks.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Physical Description:
- 1 online resource (X, 295 pages) : 157 illustrations, 72 illustrations in color.
- Edition:
- 1st ed. 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- 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.
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-44094-7
- 9783030440947
- Access Restriction:
- Restricted for use by site license.
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