226 search results - page 28 / 46 » A Convergent Reinforcement Learning Algorithm in the Continu... |
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
NIPS
2008
13 years 8 months ago
2008
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
ATAL
2006
Springer
13 years 11 months ago
2006
Springer
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
ROBOCUP
2000
Springer
13 years 11 months ago
2000
Springer
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...