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» Approximate dynamic programming: Lessons from the field
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CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 7 months ago
Mean field for Markov Decision Processes: from Discrete to Continuous Optimization
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Nicolas Gast, Bruno Gaujal, Jean-Yves Le Boudec
IJCNN
2008
IEEE
14 years 1 months ago
A quantum calculus formulation of dynamic programming and ordered derivatives
— Much recent research activity has focused on the theory and application of quantum calculus. This branch of mathematics continues to find new and useful applications and there ...
John Seiffertt, Donald C. Wunsch
ATAL
2010
Springer
13 years 2 months ago
Approximate dynamic programming with affine ADDs
The Affine ADD (AADD) is an extension of the Algebraic Decision Diagram (ADD) that compactly represents context-specific, additive and multiplicative structure in functions from a...
Scott Sanner, William T. B. Uther, Karina Valdivia...
NIPS
2008
13 years 8 months ago
Biasing Approximate Dynamic Programming with a Lower Discount Factor
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
Marek Petrik, Bruno Scherrer
HICSS
2009
IEEE
108views Biometrics» more  HICSS 2009»
14 years 1 months ago
Approximate Dynamic Programming in Knowledge Discovery for Rapid Response
One knowledge discovery problem in the rapid response setting is the cost of learning which patterns are indicative of a threat. This typically involves a detailed follow-through,...
Peter Frazier, Warren B. Powell, Savas Dayanik, Pa...