About the GPEMjournal blog

This is the editor's blog for the journal Genetic Programming and Evolvable Machines. The official web site for the journal, maintained by the publisher (Springer) is here. The GPEMjournal blog is authored and maintained by Lee Spector.

Friday, December 31, 2021

Call for Papers: Thirtieth Anniversary of Genetic Programming: On the Programming of Computers by Means of Natural Selection

In 1992, John R. Koza published his first book on Genetic Programming (GP): "Genetic Programming: On the Programming of Computers by Means of Natural Selection" [1]. This ground-breaking book paved the way for the establishment of a new field of study. It influenced the work of thousands of researchers and practitioners worldwide, many of whom aimed to continue the exploration, formalization and improvement of the original formulation of GP and/or to apply GP to challenging problems.  

We aim to celebrate the 30th anniversary of [1] with a special issue that focuses on the multiple impacts that the book had, and is still having, on the GP field. We hope that the special issue will illustrate many of the ways in which the ideas proposed by Koza in [1] have influenced and are still influencing the GP community. 

[1] Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA, USA: MIT Press. ISBN: 0-262-11170-5


We are open to a broad range of submissions that, in various ways, help us better understand the impact of [1] on the GP community. Submissions that would be welcomed might for example present: 

  • High quality review articles of [1] and of subsequent books or other types of publications, that may include a deep discussion of the relationship, similarities and differences with [1].
  • Discussions of ways in which current techniques and practices are similar to or different from those recommended in [1], and the ways in which the methods presented in [1] have evolved towards more modern and effective methods.
  • Challenges that [1] regarded as open, and the extent to which they are now completely fulfilled or that still constitute open issues for the GP field. 
  • Ground-breaking ideas that were proposed in [1] and that have inspired research in the past, or may inspire new research in the future.
  • Ideas in [1] that have received little attention to date, which might be beneficial to revisit.
  • Works that deal with the impact that [1] has had in applied domains, exploring and/or surveying the achievements and limits of the methods and ideas proposed in [1] for solving real-world problems.
  • Applications that directly build on the techniques described in [1] and are able to achieve human-competitive results.


  • Submission deadline: 30 July 2022
  • Initial reviews: 15 October 2022
  • Resubmissions: 10 December 2023
  • Final notifications: 10 February 2023


Leonardo Vanneschi 
NOVA IMS, Universidade Nova de Lisboa, Portugal

Leonardo Trujillo 
Instituto Tecnológico de Tijuana, Mexico


Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. All papers will be reviewed following standard reviewing procedures for the Journal. Papers must be prepared in accordance with the Journal guidelines: www.springer.com/10710.

Submit manuscripts to: http://GENP.edmgr.com.  Select “S.I. Thirtieth Anniversary of Genetic Programming: On the Programming of Computers by Means of Natural Selection” as the article type or when asked if the article is for a special issue.

Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including  FAQs,  Tutorials along with Help and Support.

Additional information can be found on the official Springer Call for Papers.

Sunday, November 7, 2021

GPEM 22(4) is now available

The fourth issue of Volume 22 of Genetic Programming and Evolvable Machines is now available for download. This is a Special Issue on Highlights of Genetic Programming 2020 Events, edited by Miguel Nicolau, Ting Hu, Mengjie Zhang, and Nuno Lourenço.

It contains:

Highlights of genetic programming 2020 events
by Miguel Nicolau

Evolving continuous optimisers from scratch
by Michael A. Lones

Evolutionary algorithms for designing reversible cellular automata
by Luca Mariot, Stjepan Picek, Domagoj Jakobovic & Alberto Leporati 

A semantic genetic programming framework based on dynamic targets
by Stefano Ruberto, Valerio Terragni & Jason H. Moore 

Relationships between parent selection methods, looping constructs, and success rate in genetic programming
by Anil Kumar Saini and Lee Spector

EvoStencils: a grammar-based genetic programming approach for constructing efficient geometric multigrid methods
by Jonas Schmitt, Sebastian Kuckuk & Harald Köstler 

Semantically-oriented mutation operator in cartesian genetic programming for evolutionary circuit design
by David Hodan, Vojtech Mrazek & Zdenek Vasicek 

Evolving hierarchical memory-prediction machines in multi-task reinforcement learning
by Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf & Cedric Gondro 

Graph representations in genetic programming
by Léo Françoso Dal Piccol Sotto, Paul Kaufmann, Timothy Atkinson, Roman Kalkreuth & Márcio Porto Basgalupp 

Monday, August 23, 2021

GPEM 22(3) is now available

The third issue of Volume 22 of Genetic Programming and Evolvable Machines is now available for download.

It contains:

Feature extraction by grammatical evolution for one-class time series classification
by Stefano Mauceri, James Sweeney, Miguel Nicolau, James McDermott

Genetic programming-based regression for temporal data
by Cry Kuranga, Nelishia Pillay

Tag-based regulation of modules in genetic programming improves context-dependent problem solving
by Alexander Lalejini, Matthew Andres Moreno, Charles Ofria

Symbolic-regression boosting
by Moshe Sipper, Jason H. Moore

Software review: Pony GE2
by Tuong Manh Vu

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
by Robin Harper

Thursday, August 5, 2021


2021 Humies Winners

This year's HUMIE winners for Human-Competitive Results Produced By
Genetic And Evolutionary Computation are:

Gold:   $5000
AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real and Chen Liang and David R. So and Quoc V. Le
Presentation: http://www.human-competitive.org/sites/default/files/estebanreal.humies_video_automl_zero.mp4

Silver  $3000
Machine learning for the prediction of pseudorealistic pediatric
abdominal phantoms for radiation dose reconstruction
Marco Virgolin and Ziyuan Wang and Tanja Alderliesten and Peter A. N. Bosman and
Brian V. Balgobind and Irma W. E. M. van Dijk and
Jan Wiersma and Petra S. Kroon and Gert O. Janssens and
Marcel van Herk and David C. Hodgson and Lorna Zadravec Zaletel and
Coen R. N. Rasch and Arjan Bel
Presentation: http://www.human-competitive.org/sites/default/files/humies2021_virgolin_1.mp4

Bronze: $2000
An evolutionary approach for generating software models: The case of
Kromaia in game software engineering
Daniel Blasco and Jaime Font and Mar Zamorano and Carlos Cetina
Presentation: http://www.human-competitive.org/sites/default/files/font_for_humies.107mb.mp4

Details of the winners, finalists and all 20 entries are given on the
Annual "Humies" Awards For Human-Competitive Results web pages

Thursday, June 3, 2021

GPEM 22(2) is now available

The second issue of Volume 22 of Genetic Programming and Evolvable Machines is now available for download.

It contains:

Discovering novel memory cell designs for sentiment analysis on tweets
by Sergiu Cosmin Nistor, Mircea Moca, Răzvan Liviu Nistor

An enhanced Huffman-PSO based image optimization algorithm for image steganography
by Neha Sharma, Usha Batra

TPOT-NN: augmenting tree-based automated machine learning with neural network estimators
by Joseph D. Romano, Trang T. Le, Weixuan Fu, Jason H. Moore

Efficiency improvement of genetic network programming by tasks decomposition in different types of environments
by Mohamad Roshanzamir, Maziar Palhang, Abdolreza Mirzaei

Thursday, March 18, 2021

CfP: Trust, Trustworthiness, and Evolvable Systems

Anikó Ekárt and Peter R. Lewis will guest edit a special issue on Trust, Trustworthiness, and Evolvable Systems. 

See the full call for papers at https://www.springer.com/journal/10710/updates/18975534.

Saturday, February 27, 2021

GPEM 22(1) is now available

The first issue of Volume 22 of Genetic Programming and Evolvable Machines is now available for download.

It contains:

Editorial introduction
by Lee Spector

Acknowledgement to reviewers (2020)
by Lee Spector

Benchmarking state-of-the-art symbolic regression algorithms
by Jan Žegklitz, Petr Pošík

Stock selection heuristics for performing frequent intraday trading with genetic programming
by Alexander Loginov, Malcolm Heywood, Garnett Wilson

Choosing function sets with better generalisation performance for symbolic regression models
by Miguel Nicolau, Alexandros Agapitos

Fuzzy cognitive maps for decision-making in dynamic environments
by Tomas Nachazel

Virginia Dignum: Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way
by Nicolas E. Gold

Tim Taylor and Alan Dorin: Rise of the self-replicators—early visions of machines, AI and robots that can reproduce and evolve
by Stefano Nichele