181 search results - page 23 / 37 » On Policy Learning in Restricted Policy Spaces |
MICAI
2010
Springer
13 years 6 months ago
2010
Springer
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
NIPS
2003
13 years 9 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...
IJRR
2008
13 years 7 months ago
2008
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...