随机动态规划 meaning in Chinese
stochastic dynamic programming
Examples
- Sdp with successive approximations and its application in the operation optimization of multireservoir system
逐次逼近随机动态规划及库群优化调度 - The first - passage time of controlled quasi - hamilton systems have been studied by using the stochastic averaging method for quasi - hamitonian systems and the stochastic dynamical programming principle
本文利用拟hamilton系统的随机平均法及随机动态规划原理研究了具有控制的拟hamilton系统的首次穿越问题。 - Markov decision process , in short mdp , is also called sequential stochastic optimization stochastic optimum control . the controlled markov process or stochastic dynamic programming is the theory on stochastic sequential decision
马尔可夫决策过程( markovdecisionprocesses ，简称mdp ，又称序贯随机最优化、随机最优控制、受控的马尔可夫过程或随机动态规划)是研究随机序贯决策的问题的理论。 - In continuous - lime framework , assuming that asset price follows stochastic diffusion process , it introduces parametric uncertainty , and applies stochastic dynamic programming to derive the closed - form solution of optimal portfolio choice , which maximizes the expected power utility of investor ' s terminal wealth ; in discrete - time framework , continuous compounding monthly returns of risky asset are assumed to be normal i . 1 . d . , it applies the rule of bayesian learning to do empirical study about two different sample of shanghai exchange composite index
在连续时间下假设资产的价格服从随机扩散过程，引入参数不确定性，利用随机动态规划方法推导出风险资产最优配置的封闭解，使投资者的终期财富期望幂效用最大；在离散时间下假设风险资产的连续复合月收益率服从独立同分布的正态分布，通过贝叶斯学习准则，以上证综合指数不同区间段的两个样本做实证研究。 - Then , the dynamical programming equations and their associated boundary and final time conditions for the problems of maximization of reliability and of maximization of mean first - passage time are formulated . the optimal control laws are " bang - bang " controls which are derived from the dynamical programming equations and the control constraints
然后利用随机平均法及随机动态规划原理导出了以最大可靠性为目标的随机最优控制策略，说明了当控制力为有界函数时，随机最优控制即是bang - bang控制。