125 search results - page 2 / 25 » Reinforcement Learning in Continuous Time and Space |
MICAI
2009
Springer
13 years 11 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...
ICMLA
2004
13 years 6 months ago
2004
We present JoSTLe, an algorithm that performs value iteration on control problems with continuous actions, allowing this useful reinforcement learning technique to be applied to p...
ICML
2000
IEEE
14 years 5 months ago
2000
IEEE
NIPS
2003
13 years 6 months ago
2003
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
ICANNGA
2007
Springer
13 years 11 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...