Large Deviations for Diffusions Depending on Small Parameters: A Stochastic Control Method.

1978 ◽  
Author(s):  
Wendell H. Fleming
Keyword(s):  
Large Deviations ◽  
Stochastic Control ◽  
Control Method ◽  
Small Parameters

scholarly journals Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Yan Chen ◽  
Yingchun Deng ◽  
Shengjie Yue ◽  
Chao Deng
Keyword(s):  
Stochastic Control ◽  
Optimal Trajectory ◽  
Control Method ◽  
Dimensional Space ◽  
Target Position ◽  
Movement Trajectory ◽  
Linear Dynamical Systems ◽  
Reaching Movement ◽  
Optimal Velocity ◽  
Straight Line

This paper considers a d-dimensional stochastic optimization problem in neuroscience. Suppose the arm’s movement trajectory is modeled by high-order linear stochastic differential dynamic system in d-dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.

scholarly journals TIME-INCONSISTENT MARKOVIAN CONTROL PROBLEMS UNDER MODEL UNCERTAINTY WITH APPLICATION TO THE MEAN-VARIANCE PORTFOLIO SELECTION

2021 ◽  
pp. 2150003
Author(s):  
TOMASZ R. BIELECKI ◽  
TAO CHEN ◽  
IGOR CIALENCO
Keyword(s):  
Stochastic Control ◽  
Portfolio Selection ◽  
Model Uncertainty ◽  
Control Method ◽  
Learning Algorithm ◽  
Control Problems ◽  
The Mean ◽  
Time Inconsistent ◽  
Mean Variance Portfolio ◽  
Mean Variance

In this paper, we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfect strategies with the adaptive robust stochastic control method to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results and by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

A distributed access control method for wireless LANs in shadowing environments

2001 ◽  
Vol 84 (9) ◽  
pp. 16-26
Author(s):  
Tadao Saito ◽  
Hitoshi Aida ◽  
Terumasa Aoki ◽  
Soichiro Hidaka ◽  
Tredej Toranawigtrai ◽  
...  
Keyword(s):  
Access Control ◽  
Control Method ◽  
Wireless Lans ◽  
Distributed Access Control
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