495 search results - page 6 / 99 » Constructing States for Reinforcement Learning |
AAMAS
2002
Springer
13 years 6 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
ICML
1996
IEEE
13 years 11 months ago
1996
IEEE
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
ICMLA
2008
13 years 8 months ago
2008
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
ICML
2000
IEEE
14 years 7 months ago
2000
IEEE
We explore combining reinforcement learning with a hand-crafted local controller in a manner suggested by the chaotic control algorithm of Vincent, Schmitt and Vincent (1994). A c...
AUSAI
2005
Springer
14 years 14 days ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...