18 search results - page 1 / 4 » Global Reinforcement Learning in Neural Networks with Stocha... |
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
NECO
2007
13 years 4 months ago
2007
The persistent modification of synaptic efficacy as a function of the relative timing of pre- and postsynaptic spikes is a phenomenon known as spiketiming-dependent plasticity (...
EVOW
2003
Springer
13 years 9 months ago
2003
Springer
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
SYNASC
2005
IEEE
13 years 10 months ago
2005
IEEE
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
JMLR
2008
13 years 4 months ago
2008
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...