A stochastic evolutionary neuron migration process with emerged Hebbian dynamics
Janne Haverinen, Juha Röning · 2002
In this paper, we propose a phenomenological developmental model based on a stochastic evolutionary neuron migration process (SENMP). Employing a spatial encoding scheme with lateral interaction of neurons for artificial neural networks representing candidate solutions within a neural network ensemble , neurons of the ensemble form problem-specific geometrical structures as they migrate under selective pressure. The SENMP is applied to evolve purposeful behaviors for autonomous robots and to gain new insights into the development, adaptation and plasticity in artificial neural networks.