67 search results - page 9 / 14 » Learning predictive state representations using non-blind po... |
EPIA
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. When a robot learns to solve a goal-directed navigation task with reinforcement learning, the acquired strategy can usually exclusively be applied to the task that has be...
ALT
2010
Springer
13 years 9 months ago
2010
Springer
We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
AIIA
2007
Springer
14 years 2 months ago
2007
Springer
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
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...