| 書(shū)目名稱(chēng) | Stochastic Controls | | 副標(biāo)題 | Hamiltonian Systems | | 編輯 | Jiongmin Yong,Xun Yu Zhou | | 視頻video | http://file.papertrans.cn/878/877891/877891.mp4 | | 叢書(shū)名稱(chēng) | Stochastic Modelling and Applied Probability | | 圖書(shū)封面 |  | | 描述 | As is well known, Pontryagin‘s maximum principle and Bellman‘s dynamic programming are the two principal and most commonly used approaches in solving stochastic optimal control problems. * An interesting phenomenon one can observe from the literature is that these two approaches have been developed separately and independently. Since both methods are used to investigate the same problems, a natural question one will ask is the fol- lowing: (Q) What is the relationship betwccn the maximum principlc and dy- namic programming in stochastic optimal controls? There did exist some researches (prior to the 1980s) on the relationship between these two. Nevertheless, the results usually werestated in heuristic terms and proved under rather restrictive assumptions, which were not satisfied in most cases. In the statement of a Pontryagin-type maximum principle there is an adjoint equation, which is an ordinary differential equation (ODE) in the (finite-dimensional) deterministic case and a stochastic differential equation (SDE) in the stochastic case. The system consisting of the adjoint equa- tion, the original state equation, and the maximum condition is referred to as an (extended) Hamilto | | 出版日期 | Book 1999 | | 關(guān)鍵詞 | Martingale; Stochastic calculus; Stochastic processes; Variance; stochastic process | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4612-1466-3 | | isbn_softcover | 978-1-4612-7154-3 | | isbn_ebook | 978-1-4612-1466-3Series ISSN 0172-4568 Series E-ISSN 2197-439X | | issn_series | 0172-4568 | | copyright | Springer Science+Business Media New York 1999 |
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