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Numerical methods for stochastic control problems in continuous time. 2nd ed. (English) Zbl 0968.93005
Applications of Mathematics. 24. New York, NY: Springer. xii, 475 p. (2001).
In this second edition [for the first edition see (1992; Zbl 0754.65068)], the main change is a new chapter thirteen inserted between chapter twelve and thirteen of the previous version and the old chapter thirteen has been split into two chapters which consider deterministic problems from the point of view of the calculus of variations with finite and infinite horizon, respectively.
Chapter thirteen considers problems which have attracted the attention of research recently namely the cases of controlled variance (with applications in finance) and controlled jumps (with applications in communication). In order to obtain convergence, one has to enlarge the driving Wiener (resp. Poisson) processes by introducing the martingale measure (resp. relaxed Poisson measure).

93-02 Research exposition (monographs, survey articles) pertaining to systems and control theory
93E20 Optimal stochastic control
65K10 Numerical optimization and variational techniques
90C39 Dynamic programming
65C40 Numerical analysis or methods applied to Markov chains
93E25 Computational methods in stochastic control (MSC2010)
60J22 Computational methods in Markov chains
60J75 Jump processes (MSC2010)