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AAAI
2008
13 years 11 months ago
A Variance Analysis for POMDP Policy Evaluation
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
Mahdi Milani Fard, Joelle Pineau, Peng Sun
COR
2010
150views more  COR 2010»
13 years 9 months ago
Black box scatter search for general classes of binary optimization problems
The purpose of this paper is to apply the scatter search methodology to general classes of binary problems. We focus on optimization problems for which the solutions are represent...
Francisco Gortázar, Abraham Duarte, Manuel ...
ICCBR
2005
Springer
14 years 2 months ago
CBR for State Value Function Approximation in Reinforcement Learning
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...
Thomas Gabel, Martin A. Riedmiller
CORR
2007
Springer
87views Education» more  CORR 2007»
13 years 8 months ago
Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency
Abstract—The problem of hypothesis testing against independence for a Gauss–Markov random field (GMRF) is analyzed. Assuming an acyclic dependency graph, an expression for the...
Animashree Anandkumar, Lang Tong, Ananthram Swami
CEC
2010
IEEE
13 years 10 months ago
Optimization of biogas production with computational intelligence a comparative study
Biogas plants are reliable sources of energy based on renewable materials including organic waste. There is a high demand from industry to run these plants efficiently, which lead...
Jörg Ziegenhirt, Thomas Bartz-Beielstein, Oli...