Add to ORKGCover title.Includes bibliographical references.Supported by the NSF, with matching funds from Bellcore and Dupont. ECS-8552419 Supported by the ARO. DAAL03-86-K-0171Chee-Seng Chow, John N. Tsitsiklis
International audienceIn this work we consider the time discretization of stochastic optimal control...
The discrete-time stochastic optimal control problem is approximated by a variation of differential ...
We consider infinite horizon stochastic dynamic programs with discounted costs and study how to use ...
AbstractWe provide tight lower bounds on the computational complexity of discretetime, stationary, i...
Caption title.Bibliography: p. 13.Supported, in part, by the ARO under grant DAAL03-86-K-0171 Suppor...
Cover title. "A preliminary version of this paper was presented at the 27th IEEE Conference on decis...
Caption title.Includes bibliographical references (leaf [7]).Supported by NSF. ECS 9216531 Supported...
We consider the numerical solution of discrete-time, stationary, infinite horizon, discounted stocha...
Dynamic programming is a principal method for analyzing stochastic optimal control problems. However...
Computational complexity studies the intrinsic difficulty of solving mathematically posed problems. ...
Caption title.Includes bibliographical references (p. 40-42).Supported by the NSF. ECS 9216531 Suppo...
peer reviewedWe show that the problem of finding an optimal stochastic 'blind' controller in a Marko...
Discrete-time stochastic optimal control problems are stated over a finite number of decision stages...
Stochastic programming is the subfield of mathematical programming that considers optimization in th...
Caption title.Includes bibliographical references (p. 5-6).Supported by the ARO. DAAL03-92-G-0115Joh...
International audienceIn this work we consider the time discretization of stochastic optimal control...
The discrete-time stochastic optimal control problem is approximated by a variation of differential ...
We consider infinite horizon stochastic dynamic programs with discounted costs and study how to use ...
AbstractWe provide tight lower bounds on the computational complexity of discretetime, stationary, i...
Caption title.Bibliography: p. 13.Supported, in part, by the ARO under grant DAAL03-86-K-0171 Suppor...
Cover title. "A preliminary version of this paper was presented at the 27th IEEE Conference on decis...
Caption title.Includes bibliographical references (leaf [7]).Supported by NSF. ECS 9216531 Supported...
We consider the numerical solution of discrete-time, stationary, infinite horizon, discounted stocha...
Dynamic programming is a principal method for analyzing stochastic optimal control problems. However...
Computational complexity studies the intrinsic difficulty of solving mathematically posed problems. ...
Caption title.Includes bibliographical references (p. 40-42).Supported by the NSF. ECS 9216531 Suppo...
peer reviewedWe show that the problem of finding an optimal stochastic 'blind' controller in a Marko...
Discrete-time stochastic optimal control problems are stated over a finite number of decision stages...
Stochastic programming is the subfield of mathematical programming that considers optimization in th...
Caption title.Includes bibliographical references (p. 5-6).Supported by the ARO. DAAL03-92-G-0115Joh...
International audienceIn this work we consider the time discretization of stochastic optimal control...
The discrete-time stochastic optimal control problem is approximated by a variation of differential ...
We consider infinite horizon stochastic dynamic programs with discounted costs and study how to use ...