Stochastic control or stochastic optimal control is a subfield of control theory that deals with the existence of uncertainty either in observations of the data or in the things that drive the evolution of the data. The designer assumes, in a Bayesian probability-driven fashion, that random noise with known probability distribution affects the evolution and observation of the state variables. Stochastic control aims to design the time path of the controlled variables that performs the desired control task with minimum cost, somehow defined, despite the presence of this noise. The context may be either discrete time or continuous time.
Read more about Stochastic Control: Certainty Equivalence, Discrete Time, Continuous Time, In Finance
Famous quotes containing the word control:
“Imagine believing in the control of inflation by curbing the money supply! That is like deciding to stop your dog fouling the sidewalk by plugging up its rear end. It is highly unlikely to succeed, but if it does it kills the hound.”
—Michael D. Stephens. “On Sinai, There’s No Economics,” New York Times (Nov. 13, 1981)