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An approximation scheme for the optimal control of diffusion processes. (English) Zbl 0822.65044
A numerical approximation scheme for the infinite horizon discounted optimal control problem for a stochastic diffusion process is presented. The scheme is based on a discrete version of the dynamic programming principle and converges to the weak (viscosity) solution of the Hamilton- Jacobi-Bellman equation. The convergence is valid also when the diffusion is degenerate.
Since a diffusion leaves any bounded domain with probability 1, for the problem in \(\mathbb{R}^ n\) a truncation technique is proposed to restrict the problem to an arbitrary bounded domain. Explicit estimates of the error due to the truncation technique are proved. The method provides also approximate feedback controls at any point of the grid without extra computations. Numerical tests are given.
Reviewer: V.Arnăutu (Iaşi)

65K10 Numerical optimization and variational techniques
49L20 Dynamic programming in optimal control and differential games
49L25 Viscosity solutions to Hamilton-Jacobi equations in optimal control and differential games
49J55 Existence of optimal solutions to problems involving randomness
60J60 Diffusion processes
Full Text: DOI EuDML
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