36 search results - page 4 / 8 » Posterior Weighted Reinforcement Learning with State Uncerta... |
CDC
2008
IEEE
14 years 2 months ago
2008
IEEE
— We study the problem of dynamic learning by a social network of agents. Each agent receives a signal about an underlying state and communicates with a subset of agents (his nei...
IJCAI
2001
13 years 9 months ago
2001
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Creating coordinated multiagent policies in environments with uncertainty is a challenging problem, which can be greatly simplified if the coordination needs are known to be limi...
MICAI
2009
Springer
14 years 2 months ago
2009
Springer
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
ICIP
2001
IEEE
14 years 9 months ago
2001
IEEE
We present an approach to tracking human activities in a monocular video. We model the human body by decomposing it into torso and limbs and use simple 3D shapes to approximate th...