Democratic population decisions result in robust policy-gradient learning (Richmond et al. 2011)

This model demonstrates the use of GPU programming (with CUDA) to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and to investigate its ability to learn a simplified navigation task using a learning rule stemming from Reinforcement Learning, a policy-gradient rule.

Model Concept(s): Learning; Winner-take-all

Simulation Environment: C or C++ program

References:

Richmond P, Buesing L, Giugliano M, Vasilaki E. (2011). Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations. PloS one. 6 [PubMed]