181 search results - page 7 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
AR
2007
13 years 7 months ago
2007
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
NIPS
2007
13 years 8 months ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
ABIALS
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. In order to establish autonomous behavior for technical systems, the well known trade-off between reactive control and deliberative planning has to be considered. Within ...
ECML
2004
Springer
14 years 25 days ago
2004
Springer
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
HIS
2004
13 years 8 months ago
2004
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...