231 search results - page 7 / 47 » Active Learning in Partially Observable Markov Decision Proc... |
COLT
2000
Springer
14 years 28 days ago
2000
Springer
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process ( ¢¡¤£¦¥§ ), and focus on gradient ascent approache...
ANOR
2010
13 years 8 months ago
2010
Abstract. We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the ...
DATE
2007
IEEE
14 years 2 months ago
2007
IEEE
As the hardware and software complexity grows, it is unlikely for the power management hardware/software to have a full observation of the entire system status. In this paper, we ...
SARA
2007
Springer
14 years 2 months ago
2007
Springer
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
ATAL
2007
Springer
14 years 18 days ago
2007
Springer
In multiagent planning, it is often convenient to view a problem as two subproblems: agent local planning and coordination. Thus, we can classify agent activities into two categor...