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» Optimal Control in Large Stochastic Multi-agent Systems
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EVOW
2012
Springer
12 years 4 months ago
Hyperparameter Tuning in Bandit-Based Adaptive Operator Selection
We are using bandit-based adaptive operator selection while autotuning parallel computer programs. The autotuning, which uses evolutionary algorithm-based stochastic sampling, take...
Maciej Pacula, Jason Ansel, Saman P. Amarasinghe, ...
IJCNN
2006
IEEE
14 years 2 months ago
Optimal Design of SVC Damping Controllers with Wide Area Measurements Using Small Population based PSO
—Static Var Compensator (SVC) are employed for providing better voltage regulation and transient stability especially for increased power transfer through the transmission lines....
Tridib K. Das, Sandhya R. Jetti, Ganesh K. Venayag...
SIAMCO
2008
130views more  SIAMCO 2008»
13 years 8 months ago
Important Moments in Systems and Control
The moment problem matured from its various special forms in the late 19th and early 20th Centuries to a general class of problems that continues to exert profound influence on the...
Christopher I. Byrnes, Anders Lindquist
CDC
2010
IEEE
154views Control Systems» more  CDC 2010»
13 years 3 months ago
Distributed constrained optimization over noisy networks
In this paper we deal with two problems which are of great interest in the field of distributed decision making and control. The first problem we tackle is the problem of achieving...
Kunal Srivastava, Angelia Nedic, Dusan M. Stipanov...
CDC
2009
IEEE
132views Control Systems» more  CDC 2009»
14 years 1 months ago
Q-learning and Pontryagin's Minimum Principle
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
Prashant G. Mehta, Sean P. Meyn