Can Explainability Metrics Improve Genetic Programming? Lessons from 2048

Created by W.Langdon from gp-bibliography.bib Revision:1.9056

@InProceedings{Paul:2026:GECCOcomp,

• author = "Lauren Paul and Christina Plump and Bernhard J. Berger and Rolf Drechsler",
• title = "Can Explainability Metrics Improve Genetic Programming? Lessons from 2048",
• booktitle = "Proceedings of the 2026 Genetic and Evolutionary Computation Conference",
• year = "2026",
• editor = "Jaume Bacardit and Alexander Brownlee and Stefano Cagnoni and Martin Fyvie and Giovanni Iacca and David Walker and Leonardo Trujillo and Ting Hu and Sebastian {Rojas Gonzalez} and Saul {Calderon Ramirez} and Stephan Winkler and Yazmin Maldonado and James McDermott and Jose Manuel {Munoz Contreras} and Giorgia Nadizar and Marcella {Scoczynski Ribeiro Martins} and Hirad Assimi and Mario Andres Munoz and Oliver Cuate and Daniel Hernandez and Yanan Sun and Edgar Galvan and Aniko Ekart and Nadarajen Veerapen",
• address = "San Jose, Costa Rica",
• series = "GECCO '26",
• month = "13-17 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming",
• URL = "https://www.dfki.de/web/forschung/projekte-publikationen/publikation/17327",
• notes = "Evolutionary Computation and Explainable AI workshop: ECXAI, GECCO-2026 A Recombination of the 35th International Conference on Genetic Algorithms (ICGA) and the 31st Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Lauren Paul Christina Plump Bernhard J Berger Rolf Drechsler

Citations