000			03623nam a22005055i 4500
001			978-0-387-31071-8
003			DE-He213
005			20250710083947.0
007			cr nn 008mamaa
008			100301s2006 xxu| s |||| 0|eng d
020			_a9780387310718 _a99780387310718
024	7		_a10.1007/0-387-31071-1 _2doi
082	0	4	_a519.2 _223
100	1		_aFleming, Wendell H. _eauthor.
245	1	0	_aControlled Markov Processes and Viscosity Solutions _h[recurso electrónico] / _cby Wendell H. Fleming, H.M. Soner.
250			_aSecond Edition.
264		1	_aNew York, NY : _bSpringer New York, _c2006.
300			_aXVII, 429 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStochastic Modelling and Applied Probability, _x0172-4568 ; _v25
505	0		_aDeterministic Optimal Control -- Viscosity Solutions -- Optimal Control of Markov Processes: Classical Solutions -- Controlled Markov Diffusions in ?n -- Viscosity Solutions: Second-Order Case -- Logarithmic Transformations and Risk Sensitivity -- Singular Perturbations -- Singular Stochastic Control -- Finite Difference Numerical Approximations -- Applications to Finance -- Differential Games.
520			_aThis book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. Stochastic control problems are treated using the dynamic programming approach. The authors approach stochastic control problems by the method of dynamic programming. The fundamental equation of dynamic programming is a nonlinear evolution equation for the value function. For controlled Markov diffusion processes, this becomes a nonlinear partial differential equation of second order, called a Hamilton-Jacobi-Bellman (HJB) equation. Typically, the value function is not smooth enough to satisfy the HJB equation in a classical sense. Viscosity solutions provide framework in which to study HJB equations, and to prove continuous dependence of solutions on problem data. The theory is illustrated by applications from engineering, management science, and financial economics. In this second edition, new material on applications to mathematical finance has been added. Concise introductions to risk-sensitive control theory, nonlinear H-infinity control and differential games are also included. Review of the earlier edition: "This book is highly recommended to anyone who wishes to learn the dinamic principle applied to optimal stochastic control for diffusion processes. Without any doubt, this is a fine book and most likely it is going to become a classic on the area... ." SIAM Review, 1994
650		0	_aMATHEMATICS.
650		0	_aFINANCE.
650		0	_aSYSTEMS THEORY.
650		0	_aDISTRIBUTION (PROBABILITY THEORY).
650	1	4	_aMATHEMATICS.
650	2	4	_aPROBABILITY THEORY AND STOCHASTIC PROCESSES.
650	2	4	_aSYSTEMS THEORY, CONTROL.
650	2	4	_aCONTROL ENGINEERING.
650	2	4	_aOPERATIONS RESEARCH/DECISION THEORY.
650	2	4	_aQUANTITATIVE FINANCE.
700	1		_aSoner, H.M. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387260457
830		0	_aStochastic Modelling and Applied Probability, _x0172-4568 ; _v25
856	4	0	_uhttp://dx.doi.org/10.1007/0-387-31071-1 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c57102 _d57102