168 search results - page 3 / 34 » Reinforcement Learning Algorithm for Partially Observable Ma... |
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
ICRA
2008
IEEE
13 years 11 months ago
2008
IEEE
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
ATAL
2008
Springer
13 years 7 months ago
2008
Springer
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
GECCO
2009
Springer
13 years 3 months ago
2009
Springer
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
AIPS
2008
13 years 7 months ago
2008
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...