Talk
Evolution of network structure by temporal learning
- Kiran Kolwankar (MPI MiS Leipzig)
Abstract
We study the effect of learning dynamics on the 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 scale-free.