About this document
Genetic Programming for Explainable AI by Minh Trí is a document available to read on EtoBox.
This paper surveys the role of genetic programming (GP) in enhancing explainable artificial intelligence (XAI), highlighting its potential for improving the interpretability of machine learning models. It categorizes existing research into intrinsic interpretability, which evolves more interpretable models, and post-hoc interpretability, which explains black-box models. The paper also discusses the importance of explainability in critical applications and the challenges faced in achieving it through GP.
- Author
- Minh Trí
- Language
- EN