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» Terminating Decision Algorithms Optimally
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ML
2002
ACM
143views Machine Learning» more  ML 2002»
14 years 9 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
CDC
2010
IEEE
118views Control Systems» more  CDC 2010»
14 years 4 months ago
Distributed scheduling for air traffic throughput maximization during the terminal phase of flight
FAA's NextGen program aims at increasing the capacity of the national airspace, while ensuring the safety of aircraft. This paper provides a distributed merging and spacing al...
Rahul Chipalkatty, Philip Twu, Amir Rahmani, Magnu...
SIAMSC
2008
147views more  SIAMSC 2008»
14 years 9 months ago
Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian...
Michael P. Friedlander, Sven Leyffer