Titlebook: Stochastic Learning and Optimization; A Sensitivity-Based Xi-Ren Cao Book 2007 Springer-Verlag US 2007 Computer.Markov Chains.Markov decis

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英寸

geometrician

Xi-Ren Cao PhDuter thereafter, it was made possible to operate and control directly, through a digital controller using a microcomputer, motors, electromagnetic valves, etc. which drive the process..The controller or the control unit which consists of the microcomputer is different from the conventional controlle

DRILL

uter thereafter, it was made possible to operate and control directly, through a digital controller using a microcomputer, motors, electromagnetic valves, etc. which drive the process..The controller or the control unit which consists of the microcomputer is different from the conventional controlle

mitten

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吃掉

温顺

蜡烛

Introductionternet and wireless networks), manufacturing, logistics, robotics, and bioinformatics. Most engineering systems are too complicated to be analyzed, or the parameters of the system models cannot be easily obtained. Therefore, learning techniques have to be applied.

thwart

蒸发

Sample-Path-Based Policy Iterationand gradients can be used in gradient-based performance optimization of Markov systems. In this chapter, we show that we can use sample-path-based potential estimates in policy iteration to find optimal policies. We focus on the average-reward optimality criterion and ergodic Markov chains.