509 search results - page 2 / 102 » Compositional Models for Reinforcement Learning |
NECO
2002
13 years 4 months ago
2002
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...
ICML
1994
IEEE
13 years 8 months ago
1994
IEEE
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
CORR
1998
Springer
13 years 4 months ago
1998
Springer
A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorit...
AIIDE
2008
13 years 7 months ago
2008
Human experience with interactive games will be enhanced if the software agents that play the game learn from their failures. Techniques such as reinforcement learning provide one...
FLAIRS
2003
13 years 6 months ago
2003
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...