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ORCIDGenetic Programming and Evolvable Machines, Volume 22
Volume 22, Number 1, March 2021
- Lee Spector:
Editorial introduction. 1-2 - Lee Spector:
Acknowledgement to reviewers (2020). 3 - Jan Zegklitz
, Petr Posík:
Benchmarking state-of-the-art symbolic regression algorithms. 5-33 - Alexander Loginov, Malcolm I. Heywood, Garnett Carl Wilson:
Stock selection heuristics for performing frequent intraday trading with genetic programming. 35-72 - Miguel Nicolau, Alexandros Agapitos:
Choosing function sets with better generalisation performance for symbolic regression models. 73-100 - Tomás Nacházel:
Fuzzy cognitive maps for decision-making in dynamic environments. 101-135 - Nicolas E. Gold:
Virginia Dignum: Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. 137-139 - Stefano Nichele:
Tim Taylor and Alan Dorin: Rise of the self-replicators - early visions of machines, AI and robots that can reproduce and evolve. 141-145
Volume 22, Number 2, June 2021
- Sergiu Cosmin Nistor, Mircea Moca, Razvan Liviu Nistor:
Discovering novel memory cell designs for sentiment analysis on tweets. 147-187 - Neha Sharma, Usha Batra:
An enhanced Huffman-PSO based image optimization algorithm for image steganography. 189-205 - Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore:
TPOT-NN: augmenting tree-based automated machine learning with neural network estimators. 207-227 - Mohamad Roshanzamir, Maziar Palhang, Abdolreza Mirzaei:
Efficiency improvement of genetic network programming by tasks decomposition in different types of environments. 229-266
Volume 22, Number 3, September 2021
- Stefano Mauceri, James Sweeney, Miguel Nicolau, James McDermott:
Feature extraction by grammatical evolution for one-class time series classification. 267-295 - Cry Kuranga, Nelishia Pillay:
Genetic programming-based regression for temporal data. 297-324 - Alexander Lalejini, Matthew Andres Moreno, Charles Ofria:
Tag-based regulation of modules in genetic programming improves context-dependent problem solving. 325-355 - Moshe Sipper, Jason H. Moore:
Symbolic-regression boosting. 357-381 - Tuong Manh Vu:
Software review: Pony GE2. 383-385 - Robin Harper:
Introducing Design Automation for Quantum Computing, Alwin Zulehner and Robert Wille. ISBN 978-3-030-41753-6, 2020, Springer International Publishing. 222 Pages, 51 b/w illustrations, 14 illustrations in colour. 387-389
Volume 22, Number 4, December 2021
- Miguel Nicolau:
Highlights of genetic programming 2020 events. 391-393 - Michael A. Lones:
Evolving continuous optimisers from scratch. 395-428 - Luca Mariot, Stjepan Picek, Domagoj Jakobovic, Alberto Leporati:
Evolutionary algorithms for designing reversible cellular automata. 429-461 - Stefano Ruberto, Valerio Terragni, Jason H. Moore:
A semantic genetic programming framework based on dynamic targets. 463-493 - Anil Kumar Saini, Lee Spector:
Relationships between parent selection methods, looping constructs, and success rate in genetic programming. 495-509 - Jonas Schmitt, Sebastian Kuckuk, Harald Köstler:
EvoStencils: a grammar-based genetic programming approach for constructing efficient geometric multigrid methods. 511-537 - David Hodan, Vojtech Mrazek, Zdenek Vasícek:
Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design. 539-572 - Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf, Cedric Gondro:
Evolving hierarchical memory-prediction machines in multi-task reinforcement learning. 573-605 - Léo Françoso Dal Piccol Sotto, Paul Kaufmann, Timothy Atkinson, Roman Kalkreuth, Márcio Porto Basgalupp:
Graph representations in genetic programming. 607-636
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