18 search results - page 1 / 4 » Global Reinforcement Learning in Neural Networks with Stocha... |
IJCNN
2006
IEEE
14 years 4 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 10 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
14 years 4 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
14 years 4 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 10 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...