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:
““Have we any control over being born?,” my friend asked in despair. “No, the job is done for us while we’re sleeping, so to speak, and when we wake up everything is all set. We merely appear, like an ornate celebrity wheeled out in a wheelchair.” “I don’t remember,” my friend claimed. “No need to,” I said: “what need have us free-loaders for any special alertness? We’re done for.””
—Marvin Cohen, U.S. author and humorist. The Self-Devoted Friend, New Directions (1967)