GraCo: Towards GRammar Assisted COunterfactuals

Created by W.Langdon from gp-bibliography.bib Revision:1.8564

@InProceedings{singh:2025:GECCOcomp,

• author = "Dhiraj Kumar Singh and Allan {de Lima} and Darian {Reyes Fernandez de Bulnes} and Conor Ryan",
• title = "{GraCo}: Towards {GRammar} Assisted {COunterfactuals}",
• booktitle = "Proceedings of the 2025 Genetic and Evolutionary Computation Conference Companion",
• year = "2025",
• editor = "Arnaud Liefooghe and Tapabrata Ray",
• pages = "423--426",
• address = "Malaga, Spain",
• series = "GECCO '25 Companion",
• month = "14-18 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, explainable artificial intelligence, counterfactual explanation, plausible and actionable explanation, Evolutionary Multiobjective Optimization: Poster",
• isbn13 = "979-8-4007-1464-1",
• URL = "https://doi.org/10.1145/3712255.3726604",
• DOI = "doi:10.1145/3712255.3726604",
• size = "4 pages",
• abstract = "Counterfactual explanations effectively interpret model decisions by identifying input modifications that lead to different outputs. However, generating realistic and actionable counterfactuals is challenging due to the lack of methodologies that effectively capture complex feature relationships and user-imposed constraints. This study introduces GraCo, a novel counterfactual generation (CG) method driven by Grammatical Evolution. GraCo automatically incorporates feature-domain knowledge and user preferences to generate plausible and actionable counterfactuals. We evaluate its effectiveness through empirical validation against state-of-the-art methods across multiple datasets. We propose a goodness metric for CG that accounts for class probability shifts and the differences between the counterfactual and the original input. GraCo achieves an average goodness score of 0.6231 across four datasets, outperforming all the compared approaches.",
• notes = "GECCO-2025 EMO A Recombination of the 34th International Conference on Genetic Algorithms (ICGA) and the 30th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Dhiraj Kumar Singh Allan Danilo de Lima Darian Reyes Fernandez de Bulnes Conor Ryan

Citations