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从概率角度看路径积分控制

Path integral control from probabilistic viewpoint
课程网址: http://videolectures.net/cyberstat2012_bierkens_probabilistic_vie...  
主讲教师: Joris Bierkens
开课单位: 拉德堡德大学
开课时间: 2012-10-16
课程语种: 英语
中文简介:
我们表明,涉及相对熵项的特定成本结构的随机控制问题允许纯概率解,而无需应用动态规划原理。论点如下。通过相对熵惩罚的相对于基础概率测量的随机变量的期望的最小化可以被精确地解决。在通过标准布朗运动产生随机性的情况下,该精确解可以写为Girsanov密度。 Girsanov指数中出现的随机过程具有控制过程的作用,概率测量变化的相对熵等于该过程的平方的积分。可以根据密度过程的Malliavin导数获得控制过程的显式表达式。该理论适用于最小化布朗运动的最大值(由相对熵惩罚)的问题,导致在这种情况下最优控制律的明确表达。然后将该理论应用于具有跳跃的随机过程,说明该方法的一般性。 Hamilton Jacobi Bellman方程的线性化的链接是针对扩散过程的情况。
课程简介: We show that stochastic control problems with a particular cost structure involving a relative entropy term admit a purely probabilistic solution, without the necessity of applying the dynamic programming principle. The argument is as follows. Minimization of the expectation of a random variable with respect to the underlying probability measure, penalized by relative entropy, may be solved exactly. In the case where the randomness is generated by a standard Brownian motion, this exact solution can be written as a Girsanov density. The stochastic process appearing in the Girsanov exponent has the role of control process, and the relative entropy of the change of probability measure is equal to the integral of the square of this process. An explicit expression for the control process may be obtained in terms of the Malliavin derivative of the density process. The theory is applied to the problem of minimizing the maximum of a Brownian motion (penalized by the relative entropy), leading to an explicit expression of the optimal control law in this case. The theory is then applied to a stochastic process with jumps, illustrating the generality of the method. The link to linearization of the Hamilton-Jacobi-Bellman equation is made for the case of diffusion processes.
关 键 词: 纯概率解; 相对熵项; 特定成本结构
课程来源: 视频讲座网
最后编审: 2019-03-10:cwx
阅读次数: 100