509 search results - page 6 / 102 » Compositional Models for Reinforcement Learning |
NIPS
1997
13 years 9 months ago
1997
This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
IDEAL
2007
Springer
14 years 1 months ago
2007
Springer
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
ABIALS
2008
Springer
13 years 9 months ago
2008
Springer
Factored Reinforcement Learning (frl) is a new technique to solve Factored Markov Decision Problems (fmdps) when the structure of the problem is not known in advance. Like Anticipa...
COGSR
2011
13 years 2 months ago
2011
This paper brings together work in modeling episodic memory and reinforcement learning. We demonstrate that is possible to learn to use episodic memory retrievals while simultaneo...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...