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AAMAS
2007
Springer
14 years 1 months ago
Optimal Control in Large Stochastic Multi-agent Systems
Abstract. We study optimal control in large stochastic multi-agent systems in continuous space and time. We consider multi-agent systems where agents have independent dynamics with...
Bart van den Broek, Wim Wiegerinck, Bert Kappen
JMLR
2010
161views more  JMLR 2010»
13 years 2 months ago
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
Lin Xiao
AUTOMATICA
2007
82views more  AUTOMATICA 2007»
13 years 7 months ago
Simulation-based optimal sensor scheduling with application to observer trajectory planning
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Ar...
WSC
2007
13 years 10 months ago
Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
Kuo-Hao Chang, L. Jeff Hong, Hong Wan
GLVLSI
2005
IEEE
118views VLSI» more  GLVLSI 2005»
14 years 1 months ago
A continuous time markov decision process based on-chip buffer allocation methodology
We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...