Stochastic Control of Hereditary Systems and Applications
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 memor...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2008, 2008
|
| Edition: | 1st ed. 2008 |
| Series: | Stochastic Modelling and Applied Probability
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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 |
|---|---|
| Physical Description: | XVIII, 406 p online resource |
| ISBN: | 9780387758169 |