Papers
A (currently only sorted by date) list of papers relevant to EC and XAI. Please send suggestions for papers relevant to both EC and XAI to alexander dot brownlee at stir dot ac dot uk.
2023
Evolutionary Approaches to Explainable Machine Learning. Ryan Zhou and Ting Hu. [https://arxiv.org/abs/2306.14786]
Genetic Algorithm with Linkage Learning. Renato Tinós, Michal Przewozniczek, Darrell Whitley, Francisco Chicano. GECCO 2023. [https://doi.org/10.1145/3583131.3590349]
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models. Lennart Schneider, Bernd Bischl, Janek Thomas. GECCO 2023. [https://doi.org/10.1145/3583131.3590380]
Improving Shoreline Forecasting Models with Multi-Objective Genetic Programming. Mahmoud Al Najar, Rafael Almar, Erwin W. J. Bergsma, Jean-Marc Delvit, Dennis G. Wilson. [https://eartharxiv.org/repository/object/4899/download/9722/]
Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image Analysis Kévin Cortacero, Brienne McKenzie, Sabina Müller, Roxana Khazen, Fanny Lafouresse, Gaëlle Corsaut, Nathalie Van Acker, François-Xavier Frenois, Laurence Lamant, Nicolas Meyer, Béatrice Vergier, Dennis G. Wilson, Hervé Luga, Oskar Staufer, Michael L. Dustin, Salvatore Valitutti, Sylvain Cussat-Blanc. [https://arxiv.org/abs/2302.14762]
Explaining a Staff Rostering Genetic Algorithm using Sensitivity Analysis and Trajectory Analysis. Martin Fyvie, John A.W. McCall, Lee A. Christie, Alexander E.I. Brownlee. ECXAI workshop @ GECCO 2023
From Fitness Landscapes to Explainable AI and Back. Sarah L. Thomson, Jason Adair, Alexander E.I. Brownlee, Daan van den Berg. ECXAI workshop @ GECCO 2023
Towards Principled Synthetic Benchmarks for Explainable Rule Set Learning Algorithms. David Pätzel, Michael Heider, Jörg Hähner. ECXAI workshop @ GECCO 2023
Evolutionary Computation and Explainable AI: a year in review. Bacardit, J., Brownlee, A.E.I., Cagnoni, S., Iacca, G., McCall, J.A.W., Walker, D. Late-breaking Abstracts, EvoStar Conference 2023
2022
The intersection of Evolutionary Computation and Explainable AI. Jaume Bacardit, Alexander E.I. Brownlee, Giovanni Iacca, John McCall, Stefano Cagnoni, David Walker. ECXAI workshop @ GECCO 2022 Position paper presented at ECXAI workshop @ GECCO 2022 by the workshop organisers. [https://doi.org/10.1145/3520304.3533974]
Towards Explainable Metaheuristic: Mining Surrogate Fitness Models for Importance of Variables. Manjinder Singh, Alexander Brownlee, David Cairns. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3533966]
An Explainable Visualisation of the Evolutionary Search Process. Mathew Walter, David Walker, Matthew Craven. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3533984]
Towards the Evolutionary Assessment of Neural Transformers Trained on Source Code. Martina Saletta, Claudio Ferretti. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3534044]
Interpretable AI for policy-making in pandemics. Leonardo Lucio Custode, Giovanni Iacca. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3533959]
Evolving Explainable Rule Sets. Hormoz Shahrzad, Babak Hodjat, Risto Miikkulainen. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3534023]
Improving the Search of Learning Classifier Systems Through Interpretable Feature Clustering. Hayden Andersen, Andrew Lensen, Will N. Browne. ECXAI workshop @ GECCO 2022 [https://doi.org/10.1145/3520304.3534027]
2020
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription. Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, and Hormoz Shahrzad. GECCO 2020. [https://doi.org/10.1145/3377930.3389842]