The 29th European Conference on Genetic Programming (EuroGP) 2026 conference will take place as part of EvoStar (Evo*).
EuroGP is the premier annual conference on Genetic Programming (GP), the oldest and the only meeting worldwide devoted specifically to this branch of evolutionary computation. It is always a high-quality, enjoyable, friendly event, attracting participants from all continents, and offering excellent opportunities for networking, informal contact, and exchange of ideas with fellow researchers. It will feature a mixture of oral presentations and poster sessions and invited keynote speakers. EuroGP is featured in the conference ranking database CORE.
You can consult the proceedings of previous events at EuroGP Conference Proceedings in SpringerLink
A comprehensive bibliography of genetic programming literature and links to related material is accessible at the Genetic Programming Bibliography web page, part of the Collection of Computer Science Bibliographies maintained and managed by William Langdon, Steven Gustafson, and John Koza.
Download the CFP in PDF here.
Conference Chairs
- Luca Manzoni
Università degli studi di Trieste, Italy
lmanzoni(at)units.it - Sylvain Cussat-Blanc
Univeristy of Toulouse, France
sylvain.cussat-blanc(at)irit.fr
Publication Chair
- Qi Chen
Victoria University of Wellington, New Zeeland
qi.chen (at) vuw.ac.nz
Areas of Interest and Contributions
Topics to be covered include, but is not limited to:
- Methodological advances:
- Algorithms, representations, and operators for GP
- Surrogate models and fitness approximation in GP
- Explainability and interpretability in GP
- GP representations: tree-based, linear, graph-based, grammar-based
- Evolutionary design
- Multiple populations, coevolution, and modularity in GP
- Multi-objective GP
- Theoretical developments
- Infrastructure and Evaluation Methodologies:
- Benchmarking frameworks and reproducibility in GP
- Scalable, parallel, and distributed GP systems
- GP in embedded and resource-constrained environments
- Tools and techniques for visualization and analysis tools of GP systems
- Meta-evolution and Self-adaptation:
- Self-adaptive and self-configuring GP
- AutoML and GP-based pipeline optimization
- Meta-learning and evolution of GP parameters and operators
- Applications:
- GP for scientific discovery and symbolic modeling
- GP for continuous control and evolutionary robotics
- Real-world applications of GP in medicine, finance, etc.
- Evolvable hardware
- GP for data privacy, security, and adversarial robustness
- Genetic improvement and GP for software engineering
- Program synthesis and inductive programming via GP
- Hybrid and Unconventional Approaches:
- Hybridization of GP with other machine learning methods
- Neuroevolution and neural-GP hybrids
- Integration of GP with swarm intelligence or other evolutionary paradigms
- Unconventional GP paradigms
- Open-ended GP systems
Submission Details
Accepted papers will be published by Springer Nature in the Lecture Notes in Computer Science series. Submissions must be original and not published elsewhere. They will be peer reviewed by at least three members of the program committee. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper.
Follow these instructions to submit a paper.