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贝叶斯推理与随机控制某些可解问题的关系

On the relation between Bayesian inference and certain solvable problems of stochastic control
课程网址: http://videolectures.net/bark08_opper_otrbbi/  
主讲教师: Manfred Opper
开课单位: 柏林工业大学
开课时间: 2008-10-09
课程语种: 英语
中文简介:
非线性随机动力系统的最优控制需要非线性偏微分方程的解,即所谓的Hamilton-Jacobi-Bellman方程。最近,Bert Kappen和Emanuel Todorov已经证明,对于某些类型的成本函数,这个方程可以转换成一个线性问题,在数学上与贝叶斯估计有关。离子问题。这就产生了新的高效算法来优化控制此类系统。我将为这个令人惊讶的结果展示一个简单的证据,并讨论一些可能的影响。
课程简介: Optimal control for nonlinear stochastic dynamical systems requires thesolution of a nonlinear PDE, the so - called Hamilton Jacobi Bellman equation.Recently, Bert Kappen and Emanuel Todorov have shown that for certain types of cost functions, this equationcan be transformed to a linear problem which is mathematically related to a Bayesian estimation problem. This has led to novel efficient algorithms for optimal control of such systems. I will show a simple proof for this surprising result and discuss some possible implications.
关 键 词: 非线性随机动力系统; 偏微分方程; 成本函数; 贝叶斯估计
课程来源: 视频讲座网
最后编审: 2021-01-31:nkq
阅读次数: 49