Evolution of network structure by temporal learning
Chaotic Dynamics
2009-11-13 v1 Neurons and Cognition
Abstract
We study the effect of learning dynamics on network topology. A network of discrete dynamical systems is considered for this purpose and the coupling strengths are made to evolve according to a temporal learning rule that is based on the paradigm of spike-time-dependent plasticity. This incorporates necessary competition between different edges. The final network we obtain is robust and has a broad degree distribution.
Cite
@article{arxiv.0811.4306,
title = {Evolution of network structure by temporal learning},
author = {Juergen Jost and Kiran M. Kolwankar},
journal= {arXiv preprint arXiv:0811.4306},
year = {2009}
}
Comments
revised manuscript in communication