827 search results - page 55 / 166 » Variational methods for Reinforcement Learning |
CSE
2008
IEEE
14 years 2 months ago
2008
IEEE
Ad-hoc Grids are highly heterogeneous and dynamic networks, one of the main challenges of resource allocation in such environments is to find mechanisms which do not rely on the ...
ICMLA
2010
13 years 5 months ago
2010
Abstract-- Policy Gradients with Parameter-based Exploration (PGPE) is a novel model-free reinforcement learning method that alleviates the problem of high-variance gradient estima...
ICVS
2003
Springer
14 years 29 days ago
2003
Springer
This paper shows how to construct a linear deformable model for graph structure by performing principal components analysis (PCA) on the vectorised adjacency matrix. We commence b...
JMLR
2007
13 years 7 months ago
2007
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
GECCO
2010
Springer
13 years 11 months ago
2010
Springer
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...