Evolutionary Machine Learning Meets Self-Supervised Learning: A Comprehensive Survey
Adriano Vinhas, João Correia, Penousal Machado · IEEE Access · 2026
Research combining Evolutionary Machine Learning and Self-Supervised Learning has been steadily increasing in recent years. This suggests that combining these areas helps shaping evolutionary processes and automating the design of neural networks, while reducing the need for labelled data. However, no detailed surveys exist explaining how Evolutionary Machine Learning and Self-Supervised Learning can be used together. To help with this, we provide an overview of studies that bring these areas together, propose a definition for this area of research, and introduce a taxonomy for it. Finally, we point out some of the main challenges and suggest directions for future research.