181 search results - page 21 / 37 » On Policy Learning in Restricted Policy Spaces |
AIIA
2007
Springer
14 years 1 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...
ICMLA
2004
13 years 9 months ago
2004
In some environments, a learning agent must learn to balance competing objectives. For example, a Q-learner agent may need to learn which choices expose the agent to risk and whic...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
NIPS
2003
13 years 9 months ago
2003
Recent research has demonstrated that useful POMDP solutions do not require consideration of the entire belief space. We extend this idea with the notion of temporal abstraction. ...
ICCBR
2003
Springer
14 years 25 days ago
2003
Springer
CBR applications running in real domains can easily reach thousands of cases, which are stored in the case library. Retrieval times can increase greatly if the retrieval algorithm ...