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UAI
2003
13 years 8 months ago
Optimal Limited Contingency Planning
For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications wher...
Nicolas Meuleau, David E. Smith
NIPS
2004
13 years 8 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
JAIR
2002
120views more  JAIR 2002»
13 years 7 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
AIPS
2003
13 years 8 months ago
Synthesis of Hierarchical Finite-State Controllers for POMDPs
We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
Eric A. Hansen, Rong Zhou
ATAL
2007
Springer
13 years 11 months ago
Modeling plan coordination in multiagent decision processes
In multiagent planning, it is often convenient to view a problem as two subproblems: agent local planning and coordination. Thus, we can classify agent activities into two categor...
Ping Xuan