Neural networks and evolutionary computation. Part II: hybrid approaches in the neurosciences

For pt. I, see ibid., p. 268. This paper focuses on the intersection of neural networks and evolutionary computation. It is addressed to researchers from artificial intelligence as well as the neurosciences. It provides an overview of hybrid work done in the neurosciences, and surveys neuroscientific theories that are bridging the gap between neural and evolutionary computation. According to these theories, evolutionary mechanisms like mutation and selection act in real brains in somatic time and are fundamental to learning and developmental processes in biological neural networks.<>