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ORCID22nd EuroGP 2019: Leipzig, Germany
- Lukás Sekanina, Ting Hu, Nuno Lourenço, Hendrik Richter, Pablo García-Sánchez:
Genetic Programming - 22nd European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24-26, 2019, Proceedings. Lecture Notes in Computer Science 11451, Springer 2019, ISBN 978-3-030-16669-4
Long Presentations
- Muhammad Sheraz Anjum
, Conor Ryan:
Ariadne: Evolving Test Data Using Grammatical Evolution. 3-18 - Timothy Atkinson, Athena Karsa, John H. Drake, Jerry Swan:
Quantum Program Synthesis: Swarm Algorithms and Benchmarks. 19-34 - Riccardo Gervasi, Irene Azzali, Donal Bisanzio, Andrea Mosca, Luigi Bertolotti, Mario Giacobini:
A Genetic Programming Approach to Predict Mosquitoes Abundance. 35-48 - Ting Hu, Marco Tomassini, Wolfgang Banzhaf:
Complex Network Analysis of a Genetic Programming Phenotype Network. 49-63 - Jonathan Kelly, Erik Hemberg, Una-May O'Reilly:
Improving Genetic Programming with Novel Exploration - Exploitation Control. 64-80 - Jitka Kocnová, Zdenek Vasícek:
Towards a Scalable EA-Based Optimization of Digital Circuits. 81-97 - Ondrej Koncal, Lukás Sekanina:
Cartesian Genetic Programming as an Optimizer of Programs Evolved with Geometric Semantic Genetic Programming. 98-113 - Andrew Lensen, Bing Xue, Mengjie Zhang:
Can Genetic Programming Do Manifold Learning Too? 114-130 - James McDermott:
Why Is Auto-Encoding Difficult for Genetic Programming? 131-145 - Moshe Sipper, Jason H. Moore, Ryan J. Urbanowicz:
Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions. 146-161 - Robert J. Smith, Malcolm I. Heywood:
A Model of External Memory for Navigation in Partially Observable Visual Reinforcement Learning Tasks. 162-177 - Yu Zhang, Ting Hu, Xiaodong Liang, Mohammad Zawad Ali, Md. Nasmus Sakib Khan Shabbir:
Fault Detection and Classification for Induction Motors Using Genetic Programming. 178-193
Short Presentations
- Filipe Assunção, Nuno Lourenço, Penousal Machado, Bernardete Ribeiro:
Fast DENSER: Efficient Deep NeuroEvolution. 197-212 - Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini:
A Vectorial Approach to Genetic Programming. 213-227 - Jakub Husa:
Comparison of Genetic Programming Methods on Design of Cryptographic Boolean Functions. 228-244 - William B. Langdon, Ronny Lorenz:
Evolving AVX512 Parallel C Code Using GP. 245-261 - Luca Mariot, Domagoj Jakobovic, Alberto Leporati, Stjepan Picek:
Hyper-bent Boolean Functions and Evolutionary Algorithms. 262-277 - Thu Huong Nguyen, Andrea G. B. Tettamanzi:
Learning Class Disjointness Axioms Using Grammatical Evolution. 278-294
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