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AAAI
1996
13 years 6 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
AAAI
2010
13 years 6 months ago
Symbolic Dynamic Programming for First-order POMDPs
Partially-observable Markov decision processes (POMDPs) provide a powerful model for sequential decision-making problems with partially-observed state and are known to have (appro...
Scott Sanner, Kristian Kersting
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...
NIPS
2003
13 years 6 months ago
A Nonlinear Predictive State Representation
Predictive state representations (PSRs) use predictions of a set of tests to represent the state of controlled dynamical systems. One reason why this representation is exciting as...
Matthew R. Rudary, Satinder P. Singh