Meta learning evolutionary arti ! cial neural networks

By Ajith Abraham. 2004

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Sebastian Risi
2. Andrea Soltoggio
3. Kenneth O. Stanley
4. Jean-Baptiste Mouret
5. Paul Tonelli
6. Joel Lehman
7. Jeff Clune
8. Justin K. Pugh

Citations in the corpus

• Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, methodology): “Abraham (2004) proposed a method called Meta-Learning Evolutionary Artificial Neural Networks (MLEANN) in which evolution searches for initial weights, neural architectures and transfer functions, and finally optimizes existing learning rules.”