Graph-based Genetic Programming
Webpage: https://graphgp.com/
Description
While the classical way to represent programs in Genetic Programming (GP) is using an expression tree, different GP variants with graph-based representations have been proposed. Graph-based representations have led to novel applications of GP in circuit design, cryptography, image analysis, and more. This workshop aims to encourage this form of GP by considering graph-based methods from a unified perspective and to bringing together researchers in this subfield of GP research.
Submission format
Extended Abstracts (up to 4 pages): Are not eligible for APC - no fee paid by the authors for ACM Open Access. An Extended Abstract provides a summary of a work-in-progress, typically just enough for readers to understand the idea, scope, and potential impact. It often lacks full methodology, detailed results, or extensive references.
Important dates
- Submission opening: February 2, 2026
- Submission deadline:
March 27, 2026 April 03, 2026
- Notification: April 24, 2026
- Camera-ready: May 5, 2026
- Author's mandatory registration: May 11, 2026
ACMs new Open Access publishing model for 2026 ACM Conferences
Starting January 1, 2026, ACM will fully transition to Open Access. All ACM publications, including those from ACM-sponsored conferences, will be 100% Open Access. Authors will have two primary options for publishing Open Access articles with ACM: the ACM Open institutional model or by paying Article Processing Charges (APCs). With over 2,600 institutions already part of ACM Open, the majority of ACM-sponsored conference papers will not require APCs from authors or conferences (currently, around 76%).
Authors from institutions not participating in ACM Open will need to pay an APC to publish their papers, unless they qualify for a financial waiver. To find out whether an APC applies to your article, please consult the list of participating institutions in ACM Open and review the APC Waivers and Discounts Policy. Keep in mind that waivers are rare and are granted based on specific criteria set by ACM.
Understanding that this change could present financial challenges, ACM has approved a temporary subsidy for 2026 to ease the transition and allow more time for institutions to join ACM Open. The subsidy will offer:
- $250 APC for ACM/SIG members
- $350 for non-members
This represents a 65% discount, funded directly by ACM. Authors are encouraged to help advocate for their institutions to join ACM Open during this transition period.
This temporary subsidized pricing will apply to all conferences scheduled for 2026.
Additionally, SIGEVO will provide an additional subsidy of $125 to papers accepted to GECCO 2026 (and only for 2026) that are subject to APCs. This will make the final amounts to be paid:
- $125 (USD) for SIGEVO members
- $225 (USD) for non-members
It is IMPORTANT to mention that both forms of subsidy (by ACM and by SIGVO) only apply to GECCO 2026. Moreover, it is still to be determined how the SIGEVO subsidy will be implemented, either directly to the APC or in other forms.
Finally, we note that APC charges apply to accepted Full Papers, but Abstracts (1-2 pages), Extended Abstracts (1-4 pages) and Tutorials ARE NOT APC Eligible; i.e., an APC will not have to be paid for these types of contributions.
ACM Authorship and Peer Review Policies on Generative AI
GECCO follows the official ACM policies on authorship and peer review, including the use of generative AI tools.
Under ACM's Authorship policy, generative AI tools and technologies cannot be listed as authors of an ACM published Work. The use of generative AI tools and technologies for assistance must be fully disclosed in the manuscript's Acknowledgments section. Authors are fully accountable for the originality, accuracy, and integrity of all submitted material.
In accordance with ACM's Peer Review policy, reviewers must not upload or share submitted manuscripts or review materials with generative AI systems. Reviewers may use generative AI or tools with the sole purpose of improving the quality and readability of reviewer reports for the author.
ACM is actively developing tools to help identify improper AI use in submissions, and GECCO may employ available detection methods. Submissions found to violate ACM policies may be rejected.
-
Organizers
Travis Desell is a Professor specializing in Data Science, housed in the Department of Software Engineering in the B. Thomas Golisano College of Computing and Information Sciences (GCCIS). His research focuses on the application of machine learning to large-scale, real world data sets using high performance and distributed computing, with an emphasis on developing systems for practical scientific use. He is particularly interested in the intersection of evolutionary algorithms and neural networks, or "neuroevolution", where evolutionary algorithms are used to automate and optimize the design of neural network architectures, and is actively developing the Evolutionary eXploration of Augmenting Convolutional Toplogies (EXACT) and Evolutionary eXploration of Augmenting Memory Models algorithms in that area.
Roman Kalkreuth is currently an assistant professor at the Chair of Artificial Intelligence Methodology of Professor Holger Hoos which belongs to RWTH Aachen University in Germany. Primarily, his research focuses on the analysis and development of algorithms for graph-based genetic programming. From 2015 until 2022, he was a research associate of the Computational Intelligence Research Group of Professor Günter Rudolph at TU Dortmund University (Germany). Roman Kalkreuth defended his PhD thesis in July 2021 and then took up a postdoctoral researcher position within Professor Rudolph’s group. From October 2022 to June 2023, he worked in the Natural Computing Research Group of Professor Dr. Thomas Bäck at the Leiden Institute of Advanced Computer Science, which is part of Leiden University. He joined Laboratoire d’Informatique de Paris 6 (LIP6) of Sorbonne University in Paris as a postdoctoral researcher under supervision of Carola Doerr from June 2023 until March 2024. He then took up an assistant professor position at RWTH Aachen University, which started in April 2024.
I’m an associate professor at the University of Toulouse 1 Capitole, France, at the Institut de Recherche en Informatique de Toulouse (IRIT) and I’m part of the REVA team. I did a postdoc research working with histopathology image analysis for cancer treatment with Genetic Programming in the IRIT@CRCT group. I got my PhD degree from the University of Tsukuba, Japan. Originally, I’m from Brazil, where I did my undergraduate course, at the University of Brasilia. My research interests are related to Computational Intelligence, such as Evolutionary Computation and Artificial Life, with a greater focus on multi-objective optimization, fitness landscape and Genetic Programming. Overall, I’m interested in programs that can adapt themselves, in applications of Evolutionary Computation (black box optimization, multi-agent systems, games), as well as more speculative use of these Computational Intelligence for Artificial Life ( such as the evolution of virtual creatures and the worlds where the live).
Giorgia Nadizar is a Postdoctoral Research Fellow at the University of Toulouse Capitole, France. She obtained her Ph.D. cum laude from the University of Trieste in 2025, but has explored various research environments through internships and research visits at the Oslo Metropolitan University (Oslo), the Centrum Wiskunde & Informatica (Amsterdam), the ISAE-Supaero (Toulouse), and the MIT (Boston). Her research interests lie at the intersection of embodied AI and explainable/interpretable AI.
Giovanni Squillero is a full professor of Computer Science at Politecnico di Torino, Department of Control and Computer Engineering. His research combines artificial intelligence and soft computing, in particular bio-inspired meta-heuristics and multi-agent systems. He also designs approximate optimization techniques able to achieve acceptable solutions with reasonable amount of resources. The industrial applications of his work range from electronic CAD to bioinformatics, to the cultural sector. As of October 2024, Squillero is credited as an author in about 200 publications and as an editor in 14 volumes. He has presented several tutorials at top conferences, and he has been invited to speak at international events. Squillero was the Program Chair of EvoSTAR in 2016 and 2017. He (co-)organized the workshops on Graph Genetic Programming (GECCO24); Evolutionary Machine Learning (PPSN18); Measuring and Promoting Diversity in Evolutionary Algorithms (GECCO16-17); Evolutionary Hardware Optimization (EvoSTAR04-14). As an entrepreneur, he co-founded Ominee, S.r.l. in 2014, Bactell, Inc. in 2019, and Ai·Culture, S.r.l. in 2024.
Alberto Tonda received his Ph.D. degree in Computer Science Engineering from Politecnico di Torino, Italy, in 2011. Currently, he is a Permanent Researcher (CRCN) at the National Institute of Research for Agriculture and Environment (INRAE), and Université Paris-Saclay, Paris, France. His research interests include semi-supervised modeling of complex systems, evolutionary optimization and machine learning, with main applications in food science and biology. He led COST Action CA15118 FoodMC, a 4-year European networking project on in-silico modelling in food science. He published over 30 contributions in peer-reviewed journals, and over 60 conference papers. He was part of the program committee of 10 conferences of the domain, and he is currently an editorial board member of the journal Genetic Programming and Evolvable Machines.