Neural morphogenesis, synaptic plasticity, and evolution

By Dario Floreano, J. Urzelai. 2001

48 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Electrical and Electronic Engineering

How researchers see this paper

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

In Artificial Intelligence

1. Sebastian Risi
2. Andrea Soltoggio
3. Kenneth O. Stanley
4. Alan D. Blair
5. Oliver J. Coleman
6. Jeff Clune
7. J. Krichmar
8. Kristofor D. Carlson

In Cognitive Neuroscience

1. Sebastian Risi
2. Kenneth O. Stanley
3. Andrea Soltoggio
4. J. Krichmar
5. Alan D. Blair
6. Oliver J. Coleman
7. Nikil D. Dutt
8. Jayram Moorkanikara Nageswaran

In Electrical and Electronic Engineering

1. Sebastian Risi
2. Andrea Soltoggio
3. Kenneth O. Stanley
4. Alan D. Blair
5. Oliver J. Coleman
6. Nikil D. Dutt
7. J. Krichmar
8. Jayram Moorkanikara Nageswaran

Citations in the corpus

• Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “Another study reported that networks evolved faster, i.e., had better evolvability, when synaptic plasticity and neural architectures are evolved simultaneously (Floreano and Urzelai, 2001b).”
• An efficient automated parameter tuning framework for spiking neural networks (2014, methodology): “Alternatively, indirect encoding allows the genotype to specify a rule or method for growing the ANN instead of specifying the parameter values directly (Husbands et al., 1998; Beer, 2000; Floreano and Urzelai, 2001; Stanley and Miikkulainen, 2003).”
• Evolving Plastic Neural Networks for Online Learning: Review and Future Directions (2012, background): “Finally, it should be noted that “adaptive network” is not synonymous with “plastic network”: a network may be adaptive without having plastic synapses [11, 18, 25].”