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.
Simulation Environment: C or C++ program
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]