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PERCOM
2007
ACM
14 years 4 months ago
Sensor Scheduling for Optimal Observability Using Estimation Entropy
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Mohammad Rezaeian
IJCAI
2003
13 years 6 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
WCNC
2010
IEEE
13 years 8 months ago
Dynamic Control of Data Ferries under Partial Observations
—Controlled mobile helper nodes called data ferries have recently been proposed to bridge communications between disconnected nodes in a delay-tolerant manner. While existing wor...
Chi Harold Liu, Ting He, Kang-won Lee, Kin K. Leun...
ICML
2009
IEEE
14 years 5 months ago
Predictive representations for policy gradient in POMDPs
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
Abdeslam Boularias, Brahim Chaib-draa
IJRR
2010
162views more  IJRR 2010»
13 years 3 months ago
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...