575 search results - page 5 / 115 » Reinforcement Learning State Estimator |
103
Voted
AI
1999
Springer
14 years 9 months ago
1999
Springer
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
PRIMA
2009
Springer
15 years 4 months ago
2009
Springer
In this article, we propose a method to adapt stepsize parameters used in reinforcement learning for dynamic environments. In general reinforcement learning situations, a stepsize...
NIPS
1996
14 years 11 months ago
1996
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
NIPS
2007
14 years 11 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...
NIPS
1996
14 years 11 months ago
1996
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...