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» Observation Reduction for Strong Plans
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IJCAI
2001
13 years 9 months ago
Backbones in Optimization and Approximation
We study the impact of backbones in optimization and approximation problems. We show that some optimization problems like graph coloring resemble decision problems, with problem h...
John K. Slaney, Toby Walsh
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
ATAL
2008
Springer
13 years 9 months ago
Exploiting locality of interaction in factored Dec-POMDPs
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provabl...
Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Wh...
3DIM
2011
IEEE
12 years 7 months ago
Stereo Reconstruction of Building Interiors with a Vertical Structure Prior
—Image-based computation of a 3D map for an indoor environment is a very challenging task, but also a useful step for vision-based navigation and path planning for autonomous sys...
Bernhard Zeisl, Christopher Zach, Marc Pollefeys
ICAC
2009
IEEE
14 years 2 months ago
Injecting realistic burstiness to a traditional client-server benchmark
The design of autonomic systems often relies on representative benchmarks for evaluating system performance and scalability. Despite the fact that experimental observations have e...
Ningfang Mi, Giuliano Casale, Ludmila Cherkasova, ...