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WIOPT
2011
IEEE
13 years 1 months ago
Network utility maximization over partially observable Markovian channels
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
Chih-Ping Li, Michael J. Neely
AROBOTS
2008
166views more  AROBOTS 2008»
13 years 8 months ago
User-adapted plan recognition and user-adapted shared control: A Bayesian approach to semi-autonomous wheelchair driving
Abstract Many elderly and physically impaired people experience difficulties when maneuvering a powered wheelchair. In order to provide improved maneuvering, powered wheelchairs ha...
Eric Demeester, Alexander Hüntemann, Dirk Van...
JAIR
2002
120views more  JAIR 2002»
13 years 9 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
PERCOM
2007
ACM
14 years 9 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
ICML
1994
IEEE
14 years 1 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...