Evaluating a Novel Explainability Method for Metaheuristics via a User Study

It is easy to point out why a method should not be a black box, but it is hard to define what would make it sufficiently transparent.

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Publication Details

Journal
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Published
2025-07-14
DOI
https://doi.org/10.1145/3712255.3734337
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluating a Novel Explainability Method for Metaheuristics via a User Study

John McCall, Alexander E. I. Brownlee, G. Catalano, Russell Ainslie et al.
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Explainable Artificial Intelligence (XAI)
article

Evaluating a Novel Explainability Method for Metaheuristics via a User Study

John McCall, Alexander E. I. Brownlee, G. Catalano, Russell Ainslie, David Cairns
article en

Abstract

It is easy to point out why a method should not be a black box, but it is hard to define what would make it sufficiently transparent.

Proceedings of the Genetic and Evolutionary Computation Conference Companion
University of Stirling (GB), BT Group (United Kingdom) (GB), Robert Gordon University (GB)
BT Group
Openalex Percentile: Top 62%
Explainable Artificial Intelligence (XAI)
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