181 search results - page 27 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
ICRA
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. Many complex control problems are not amenable to traditional controller design. Not only is it difficult to model real systems, but often it is unclear what kind of beha...
ICRA
2009
IEEE
14 years 2 months ago
2009
IEEE
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose a novel dependent hierarchical Pitman-Yor process model for discrete data. An incremental Monte Carlo inference procedure for this model is developed. We show that infe...