2017

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks

Soltoggio, Andrea, Stanley, Kenneth O., Risi, Sebastian

Understand

Biological plastic neural networks are systems of extraordinary computational capabilities shaped by evolution, development, and lifetime learning.

  • The interplay of these elements leads to the emergence of adaptive behavior and intelligence.
  • Inspired by such intricate natural phenomena, Evolved Plastic Artificial Neural Networks (EPANNs) use simulated evolution in-silico to breed plastic neural networks with a large variety of dynamics, architectures, and plasticity rules: these artificial systems are composed of inputs, outputs, and plastic components that change in response to experiences in an environment.
  • These systems may autonomously discover novel adaptive algorithms, and lead to hypotheses on the emergence of biological adaptation.

Reading the bibliography…