The evolvability of artificial neural net-works for robot control

By Thomas M. Smith. 2002

12 citations recorded by the source corpus.

How researchers see this paper

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

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

Citations in the corpus

• Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, methodology): “Scientific evidence of animal learning from experience was documented initially in the works of behaviorism with scientists such as Thorndike (1911), Pavlov (1927), Skinner (1938, 1953), and Hull (1943).”
• Neuronal Plasticity and Temporal Adaptivity: GasNet Robot Control Networks (2002, background): “Similarly, generating and tuning patterns is more difficult with simple recurrent networks (Smith, 2002).”