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:
“When a book, any sort of book, reaches a certain intensity of artistic performance it becomes literature. That intensity may be a matter of style, situation, character, emotional tone, or idea, or half a dozen other things. It may also be a perfection of control over the movement of a story similar to the control a great pitcher has over the ball.”
—Raymond Chandler (1888–1959)