- author = "Roman Kalkreuth and Marie Anastacio and Anja Jankovic and Julian Dierkes and Fabricio {Olivetti de Franca} and Holger Hoos",
- title = "{GPBench}: Improving Benchmarking in Genetic Programming",
- booktitle = "Configuring and Selection of Algorithms) Workshop, COSEAL 2026",
- year = "2026",
- editor = "Holger Hoos' AIM Group",
- address = "Aachen, Germany",
- month = may # " 18-20",
- keywords = "genetic algorithms, genetic programming, TinyverseGP",
-
URL = "
https://www.coseal.net/wp-content/uploads/2026/05/COSEAL-2026-Workshop-Schedule-7.pdf",
- abstract = "Genetic Programming (GP) is a search paradigm originally proposed for program synthesis but capable of tackling multiple problem domains. Over the years, GP has evolved, with many proposed variations, especially in how they represent a solution. Current GP benchmarking initiatives are fragmented, while these different representations are rarely compared to each other. As a consequence, the community is unaware of the benefits of each representation and in which situation they perform best. To alleviate this issue, we introduce GPBench, a community-driven project that aims at improving benchmarking in GP. As a first step, we present a unified framework, dubbed TinyverseGP, which facilitates benchmarking of multiple representations and problem domains, including symbolic regression, logic synthesis and policy search",
-
notes = "There are no paper submissions and no formal
proceedings
https://www.coseal.net/coseal-workshop-2026/ https://www.coseal.net/wp-content/uploads/2026/05/COSEAL-2026-Workshop-Schedule-7.pdf",
