17 search results - page 3 / 4 » An implementation of reinforcement learning based on spike t... |
ESANN
2007
13 years 9 months ago
2007
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
HIS
2008
13 years 9 months ago
2008
Artificial Neural Networks for online learning problems are often implemented with synaptic plasticity to achieve adaptive behaviour. A common problem is that the overall learning...
IWANN
2005
Springer
14 years 29 days ago
2005
Springer
Abstract. A spiking neural network modeling the cerebellum is presented. The model, consisting of more than 2000 conductance-based neurons and more than 50 000 synapses, runs in re...
NIPS
2003
13 years 8 months ago
2003
We present test results from spike-timing correlation learning experiments carried out with silicon neurons with STDP (Spike Timing Dependent Plasticity) synapses. The weight chan...
NIPS
2008
13 years 9 months ago
2008
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...