Conference Paper (published)
Details
Citation
Thomson S, Adair J, Brownlee A & van den Berg D (2023) From Fitness Landscapes to Explainable AI and Back. In: GECCO '23 Companion. Gecco '23: The Genetic and Evolutionary Computation Conference, Lisbon, 15.07.2023-19.07.2023. New York: ACM. https://doi.org/10.1145/3583133.3596395
Abstract
We consider and discuss the ways in which search landscapes might
contribute to the future of explainable artificial intelligence (XAI),
and vice versa. Landscapes are typically used to gain insight into
algorithm search dynamics on optimisation problems; as such, it
could be said that they explain algorithms and that they are a natural
bridge between XAI and evolutionary computation. Despite this,
there is very little existing literature which utilises landscapes for
XAI, or which applies XAI techniques to landscape analysis. This
position paper reviews the existing works, discusses possible future
avenues, and advocates for increased research effort in this area
Keywords
Fitness Landscapes; Search Landscapes; Neural Networks; Explainable AI; XAI
| Status | Published |
|---|---|
| Publication date | 31/07/2023 |
| Publication date online | 24/07/2023 |
| Publisher | ACM |
| Place of publication | New York |
| ISBN | 979-8-4007-0120-7 |
| Conference | Gecco '23: The Genetic and Evolutionary Computation Conference |
| Conference location | Lisbon |
| Dates | – |
People (2)
Lecturer in Data Science, Computing Science
Senior Lecturer in Computing Science, Computing Science and Mathematics - Division