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Stochastic Control of Hereditary Systems and Applications [recurso electrónico] / edited by Mou-Hsiung Chang.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Stochastic Modelling and Applied Probability ; 59Editor: New York, NY : Springer New York, 2008Descripción: online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • recurso en línea
ISBN:
  • 9780387758169
  • 99780387758169
Tema(s): Formatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD:
  • 519.2 23
Recursos en línea:
Contenidos:
and Summary -- Stochastic Hereditary Differential Equations -- Stochastic Calculus -- Optimal Classical Control -- Optimal Stopping -- Discrete Approximations -- Option Pricing -- Hereditary Portfolio Optimization.
En: Springer eBooksResumen: This research monograph develops the Hamilton-Jacobi-Bellman (HJB) theory through dynamic programming principle for a class of optimal control problems for stochastic hereditary differential systems. It is driven by a standard Brownian motion and with a bounded memory or an infinite but fading memory. The optimal control problems treated in this book include optimal classical control and optimal stopping with a bounded memory and over finite time horizon. This book can be used as an introduction for researchers and graduate students who have a special interest in learning and entering the research areas in stochastic control theory with memories. Each chapter contains a summary. Mou-Hsiung Chang is a program manager at the Division of Mathematical Sciences for the U.S. Army Research Office.
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Item type Current library Collection Call number Status Date due Barcode
Libros electrónicos Libros electrónicos CICY Libro electrónico Libro electrónico 519.2 (Browse shelf(Opens below)) Available

and Summary -- Stochastic Hereditary Differential Equations -- Stochastic Calculus -- Optimal Classical Control -- Optimal Stopping -- Discrete Approximations -- Option Pricing -- Hereditary Portfolio Optimization.

This research monograph develops the Hamilton-Jacobi-Bellman (HJB) theory through dynamic programming principle for a class of optimal control problems for stochastic hereditary differential systems. It is driven by a standard Brownian motion and with a bounded memory or an infinite but fading memory. The optimal control problems treated in this book include optimal classical control and optimal stopping with a bounded memory and over finite time horizon. This book can be used as an introduction for researchers and graduate students who have a special interest in learning and entering the research areas in stochastic control theory with memories. Each chapter contains a summary. Mou-Hsiung Chang is a program manager at the Division of Mathematical Sciences for the U.S. Army Research Office.

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