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http://hdl.handle.net/1893/37715| Appears in Collections: | Computing Science and Mathematics Journal Articles |
| Peer Review Status: | Unrefereed |
| Title: | Introduction to the Special Issue on Explainable AI in Evolutionary Computation |
| Author(s): | Bacardit, Jaume Brownlee, Alexander Cagnoni, Stefano Iacca, Giovanni McCall, John Walker, David |
| Contact Email: | alexander.brownlee@stir.ac.uk |
| Issue Date: | Mar-2024 |
| Date Deposited: | 20-Dec-2024 |
| Citation: | Bacardit J, Brownlee A, Cagnoni S, Iacca G, McCall J & Walker D (2024) Introduction to the Special Issue on Explainable AI in Evolutionary Computation. <i>ACM Transactions on Evolutionary Learning and Optimization</i>, 4 (1), pp. 1-2. https://doi.org/10.1145/3649144 |
| Abstract: | First paragraph: Explainable Artificial Intelligence (XAI) has recently emerged as one of the most active areas of research in AI. While Evolutionary Computation (EC) is also a very active research area, the intersection between XAI and EC is still rather unexplored. This topic was the subject of our Workshops on EvolutionaryComputingandExplainableArtificialIntelligence(ECXAI) organized at GECCO 2022 and GECCO 2023. This special issue collects four articles further exploring the intersection between XAI and EC, including both, the use of EC for XAI as well as the use of explainability techniques to better understand EC methods. |
| DOI Link: | 10.1145/3649144 |
| Rights: | © ACM, 2024. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Evolutionary Learning and Optimization, 4(1), 1-2. https://doi.org/10.1145/3649144. |
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| sample-acmsmall.pdf | Fulltext - Accepted Version | 373.56 kB | Adobe PDF | View/Open |
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