250 search results - page 11 / 50 » Learning action effects in partially observable domains |
ECAI
2004
Springer
15 years 3 months ago
2004
Springer
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
ECML
2005
Springer
15 years 3 months ago
2005
Springer
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
JAIR
2007
14 years 9 months ago
2007
This paper describes Marvin, a planner that competed in the Fourth International Planning Competition (IPC 4). Marvin uses action-sequence-memoisation techniques to generate macro...
COLT
2003
Springer
15 years 2 months ago
2003
Springer
We study on-line play of repeated matrix games in which the observations of past actions of the other player and the obtained reward are partial and stochastic. We define the Part...
99
Voted
ATAL
2010
Springer
14 years 9 months ago
2010
Springer
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...