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IJCAI
2007
15 years 1 months ago
The Value of Observation for Monitoring Dynamic Systems
We consider the fundamental problem of monitoring (i.e. tracking) the belief state in a dynamic system, when the model is only approximately correct and when the initial belief st...
Eyal Even-Dar, Sham M. Kakade, Yishay Mansour
NIPS
2004
15 years 1 months ago
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
Pascal Poupart, Craig Boutilier
IAT
2005
IEEE
15 years 5 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
GLOBECOM
2007
IEEE
15 years 3 months ago
Bursty Traffic in Energy-Constrained Opportunistic Spectrum Access
We design opportunistic spectrum access strategies for improving spectrum efficiency. In each slot, a secondary user chooses a subset of channels to sense and decides whether to ac...
Yunxia Chen, Qing Zhao, Ananthram Swami
IROS
2006
IEEE
121views Robotics» more  IROS 2006»
15 years 5 months ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao