Perfect information two-person zero-sum markov games with imprecise transition probabilities

Based on an extension of the controlled Markov set-chain model by Kurano et al. (in J Appl Prob 35:293–302, 1998) into competitive two-player game setting, we provide a model of perfect information two-person zero-sum Markov games with imprecise transition probabilities. We define an equilibrium value for the games formulated with the model in terms of a partial order and then establish the existence of an equilibrium policy pair that achieves the equilibrium value. We further analyze finite-approximation error bounds obtained from a value iteration-type algorithm and discuss some applications of the model.     

Converging Marriage in Honey-Bees Optimization and Application to Stochastic Dynamic Programming

In this paper, we first refine a recently proposed metaheuristic called “Marriage in Honey-Bees Optimization” (MBO) for solving combinatorial optimization problems with some modifications to formally show that MBO converges to the global optimum value. We then adapt MBO into an algorithm called “Honey-Bees Policy Iteration” (HBPI) for solving infinite horizon-discounted cost stochastic dynamic programming problems and show that HBPI also converges to the optimal value.     

New reals: Can live with them,can live without them

We give a self‐contained proof of the preservation theorem for proper countable support iterations known as “tools‐preservation”, “Case A” or “first preservation theorem” in the literature. We do not assume that the forcings add reals. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

几乎各向同性的高维空间分数阶扩散方程的分块快速正则Hermite分裂预处理方法

一类空间分数阶扩散方程经过有限差分离散后所得到的离散线性方程组的系数矩阵是两个对角矩阵与Toeplitz型矩阵的乘积之和.在本文中,对于几乎各向同性的二维或三维空间分数阶扩散方程的离散线性方程组,采用预处理Krylov子空间迭代方法,我们利用其系数矩阵的特殊结构和具体性质构造了一类分块快速正则Hermite分裂预处理子.通过理论分析,我们证明了所对应的预处理矩阵的特征值大部分都聚集于1的附近.数值实验也表明,这类分块快速正则Hermite分裂预处理子可以明显地加快广义极小残量(GMRES)方法和稳定化的双共轭梯度(BiCGSTAB)方法等Krylov子空间迭代方法的收敛速度.     

M-矩阵平方根的一类迭代法

矩阵平方根在数学的许多应用中起着重要的作用.本文研究M-矩阵平方根的计算问题,提出一种计算正则M-矩阵平方根的迭代方法.首先将这个问题转化为M-矩阵代数Riccati方程,进而提出一种有效的方法来求解这个特殊的MARE.理论分析表明,该方法在一定条件下是收敛的.数值实验表明该方法是可行的,且优于二项式迭代法.     

高次非球面光路计算中的两个重要问题

提出在高次非球面的光路计算中运用变曲率的“辅助球面”概念,对某些文献在此方面存在的问题进行分析,提出迭代逼近精度的数值判据及浮动处理方法。     

Root determination by use of Padé approximants

In this paper we describe a new technique for generating iteration formulas — of arbitrary order — for determining a zero (assumed simple) of a functionf, assumed analytic in a region containing the zero. The 1/p Padé Approximant (p0) to the functiong(t)f(z) is formed wherez=w+t, using the Taylor series forf at the pointw, an approxination to the zero off. The value oft for which the 1/p Padé Approximant vanishes provides the basis of iteration formulas of orderp+2.Some known iteration formulas, e.g., Newton-Raphson's, Halley's and Kiss's of order of convergence two, three and four, are directly obtained by settingp=0,1 and 2, respectively.     

用方阵乘幂求和法求线性方程组的数值解

介绍了一种新型的,不同于传统的雅克比或高斯塞德尔迭代法的,求解线性方程组的方阵乘幂求和法,并引入了方阵意义上求积分的龙贝格法.该算法成立须以方阵A为实阵,非奇异且主对角元素占优.该法较雅克比或高斯塞德尔迭代的计算量小,特别有助于求解大型线性方程组的问题.     

Optimal Synthesis of Steel Frameworks Using Standard Sections* †

This paper presents a computer-based method for optimally sizing members of planar steel frameworks using commercially available standard sections. For first-order behavior and static loads, a minimum-weight structure is found while simultaneously ensuring stress and displacement performance conditions under applied service loads. Architectural conditions are imposed on section sizes to satisfy fabrication requirements related to member continuity and structure symmetry. The design method presented is iterative in nature and remarkably efficient. The number of iterations is generally quite small and almost totally independent: of the complexity of the structure. Designs are presented for two steel frameworks that are typical of those encountered in professional practise.     

逼近Banach空间中渐近非扩张映象的不动点

设E是一致凸Banach空间,C是E的非空闭凸子集, T:C→C是具有不动点的渐近非扩张映象. 该文证明了, 在某些适当的条件下, 由下列修改了的Ishikawa迭代程序所定义的序列{x\-n},\$\$x\-\{n+1\}=t\-nT\+n(s\-nT\+nx\-n+(1-s\-n)x\-n)+(1-t\-n)x\-n,\$\$弱收敛到T的不动点, 其中{t\-n},{s\-n}是区间\[0,1\]中满足某些限制的实数列.