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» Approximations in Distributed Optimization
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AIPS
2006
15 years 8 months ago
Sequential Monte Carlo in Probabilistic Planning Reachability Heuristics
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
AI
2008
Springer
15 years 6 months ago
Sequential Monte Carlo in reachability heuristics for probabilistic planning
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
PPOPP
2011
ACM
14 years 9 months ago
Compact data structure and scalable algorithms for the sparse grid technique
The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data...
Alin Florindor Murarasu, Josef Weidendorfer, Gerri...
BMCBI
2007
154views more  BMCBI 2007»
15 years 6 months ago
Bounds on the distribution of the number of gaps when circles and lines are covered by fragments: Theory and practical applicati
Background: The question of how a circle or line segment becomes covered when random arcs are marked off has arisen repeatedly in bioinformatics. The number of uncovered gaps is o...
John Moriarty, Julian R. Marchesi, Anthony Metcalf...
AMAI
2006
Springer
15 years 6 months ago
Symmetric approximate linear programming for factored MDPs with application to constrained problems
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
Dmitri A. Dolgov, Edmund H. Durfee