70 search results - page 9 / 14 » Adaptive Importance Sampling Technique for Markov Chains Usi... |
ASMTA
2008
Springer
13 years 9 months ago
2008
Springer
The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of paralle...
TROB
2010
13 years 5 months ago
2010
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
CDC
2009
IEEE
14 years 6 days ago
2009
IEEE
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
ICCV
2011
IEEE
12 years 4 months ago
2011
IEEE
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...
CPAIOR
2008
Springer
13 years 9 months ago
2008
Springer
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...