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AAAI
2010
13 years 9 months ago
Understanding the Success of Perfect Information Monte Carlo Sampling in Game Tree Search
Perfect Information Monte Carlo (PIMC) search is a practical technique for playing imperfect information games that are too large to be optimally solved. Although PIMC search has ...
Jeffrey Richard Long, Nathan R. Sturtevant, Michae...
ICRA
1999
IEEE
126views Robotics» more  ICRA 1999»
13 years 12 months ago
Monte Carlo Localization for Mobile Robots
Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilisticlocalization algorithms known as Monte...
Frank Dellaert, Dieter Fox, Wolfram Burgard, Sebas...
AIPS
2006
13 years 9 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
13 years 7 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
PRL
2006
163views more  PRL 2006»
13 years 7 months ago
3D target recognition using cooperative feature map binding under Markov Chain Monte Carlo
A robust and effective feature map integration method is presented for infrared (IR) target recognition. Noise in an IR image makes a target recognition system unstable in pose es...
Sungho Kim, In-So Kweon