Order Environments of Topological Spaces

In this paper it is proved that a space may be realized as the set of the maximal elements in a continuous poset if and only if it is Tychonoff.     

依状态独立的随机环境中的马氏链

本主要讨论了依状态独立的随机环境中的马氏链，并严格地证明了依状态独立的随机环境中的马氏链，如果在环境不退化的一般情形下，不是时齐马氏链，而环境退化必然是马氏链这个结论。     

随机环境中分枝q-过程

引进了机环境中一致马氏过程,随机分枝q-矩阵和随机环境中分枝q-过程.给了随机环境中分枝q-过程存在性和唯一性的充分条件.最后证明了任意随机分枝转移密度矩阵都是零流入的.     

变化环境中的分枝过程

设｛犣狀｝为变化环境中的上临界的分枝过程，犠为非负鞅｛犣狀／犈犣狀｝的极限，在一致上临界以及控制后代分布尾行为的假设条件下，给出了犠非退化的必要条件，且证明了｛犣狀／犈犣狀｝的犔１ 收敛性质成立．     

Supporting Learning in Evolving Dynamic Environments

In dynamic decision environments such as direct sales, customer support, and electronically mediated bargaining, decision makers execute sequences of interdependent decisions under time pressure. Past decision support systems have focused on substituting for decision makers' cognitive deficits by relieving them of the need to explicitly account for sequential dependencies. However, these systems themselves are fragile to change and, further, do not enhance decision makers' own adaptive capacities. This study presents an alternative strategy that defines information systems requirements in terms of enhancing decision makers' adaptation. In so doing, the study introduces a simulation model of how decision makers learn patterns of sequential dependency. When a system was used to manage workflows in a way predicted by the model to enhance learning, decision makers in a bargaining experiment learned underlying patterns of sequential dependencythat helped them adapt to new situations. This result is rare if not unique in the study of dynamic decision environments. It indicates that a shift, away from substituting for short-term deficits and toward enhancing pattern learning, can substantially improve the effectiveness of decision support in dynamic environments. Based on the specific findings in this study, this shift has important implications for designing information system workflows and potential future applications in interface design.     

模糊环境下的最优装载问题

将动态规划中的一维背包问题推广到了n维,并利用模糊数为工具,在模糊环境下给出了n维背包问题的最优解,最后通过实例说明该方法的简便、有效和实用性.     

Evaluating Information in Ill-Structured Decision Environments

The issue of evaluating information in an ill-structured decision environment is examined by comparing four alternative methods. Two are derived from the cognitive maps of the decision-makers: one is based on the intrinsic variety of the factor being evaluated, and the other on the number of links in the cognitive map that are affected by the factor's removal. The other two involve Likert scale and rank-ordering questions to measure the value of the factor directly. The four methods were tested using 10 district claim managers of an insurance company. The task involved evaluating the performance of their subordinates. The results were inconclusive, as no one measure clearly dominated the others. However, analyses of post-experiment interviews suggest that the decision-makers' evaluation of the information content of the relevant factors was inversely related to the ease with which they could infer the state (value) of a factor.     

Nonlinear Filtering for Diffusions in Random Environments

Suppose that the signal X to be estimated is a diffusion process in a random medium W and the signal is correlated with the observation noise. We study the historical filtering problem concerned with estimating the signal path up until the current time based upon the back observations. Using Dirichlet form theory, we introduce a filtering model for general rough signal X ^W and establish a multiple Wiener integrals representation for the unnormalized pathspace filtering process. Then, we construct a precise nonlinear filtering model for the process X itself and give the corresponding Wiener chaos decomposition.     

Dynamic Global Constraints in Backtracking Based Environments

Global constraints provide strong filtering algorithms to reduce the search space when solving large combinatorial problems. In this paper we propose to make the global constraints dynamic, i.e., to allow extending the set of constrained variables during search. We describe a generic dynamisation technique for an arbitrary monotonic global constraint and we compare it with the semantic-based dynamisation for the alldifferent constraint. At the end we sketch a dynamisation technique for non-monotonic global constraints. A comparison with existing methods to model dynamic problems is given as well.     

双无限随机环境中的常返马氏链

对双无限随机环境中的马氏链,给出了常返的两种可能的定义,讨论了它们间的联系和基本性质,给出了状态或链为常返的判断准则.讨论了双无限随机环境中马氏链的不变测度的存在性,首次给出了双无限随机环境中马氏链的正常返及零常返的概念,并讨论了其相关性质.特别地,应用不变函数的性质,给出了状态具有正常返性或零常返性的判断准则.     

Multiphasic Individual Growth Models in Random Environments

The evolution of the growth of an individual in a random environment can be described through stochastic differential equations of the form dY _t  = β(α − Y _t )dt + σdW _t , where Y _t  = h(X _t ), X _t is the size of the individual at age t, h is a strictly increasing continuously differentiable function, α = h(A), where A is the average asymptotic size, and β represents the rate of approach to maturity. The parameter σ measures the intensity of the effect of random fluctuations on growth and W _t is the standard Wiener process. We have previously applied this monophasic model, in which there is only one functional form describing the average dynamics of the complete growth curve, and studied the estimation issues. Here, we present the generalization of the above stochastic model to the multiphasic case, in which we consider that the growth coefficient β assumes different values for different phases of the animal’s life. For simplicity, we consider two phases with growth coefficients β ₁ and β ₂. Results and methods are illustrated using bovine growth data.     

随机环境中随机指标分枝过程矩的渐近性

引入了随机环境中随机指标分枝过程模型,证明了该模型矩的渐近性。     

Bisexual Galton-Watson Branching Processes in Random Environments

In this paper, we consider a bisexual Galton-Watson branching process whose offspring probability distribution is controlled by a random environment proccss. Some results for the probability generating functions associated with the process are obtained and sufficient conditions for certain extinction and for non-certain extinction are established.     

模糊环境下美式看跌期权的定价研究

应用模糊集理论将无风险利率和波动率进行模糊化,以梯形模糊数替代精确值,将美式期权的定价模型扩展到美式期权模糊定价模型.得到了模糊风险中性概率表达式,并在此概率测度下推导出多期二叉树模糊定价模型,以及二叉树上各节点以梯形模糊数表示的模糊期权价值,以数值模拟演示了美式看跌期权的模糊定价过程.最后分析了不同风险偏好投资者在不确定环境下的套利决策行为,结果表明风险偏好大的投资者具有较高的置信水平、较小的主观模糊期权价格以及较大的无风险套利区间.     

一类随机环境中的随机游动

在Solomn的模型的基础上对一类随机环境中随机游动进行了讨论，并得出了一个常返性准则和一些极限性质。     

时间随机环境下随机游动的渐近行为

本文给出了可数状态空间中时间随机环境下随机游动的一个统一的模型 .对于最常见的情况 ,即d维最近邻域随机环境下随机游动 ,如果环境是严平稳的 ,则在一定条件下 ,该随机游动满足强大数定律和中心极限定理 .特别地 ,当环境独立同分布时 ,我们可以得到更为具体的结果 ,该结果类似于经典的随机游动的相应结论 .     

独立平稳随机环境中的P—S—D分枝过程

本文研究了独立同分布的随机环境中的Ｐ－Ｓ－Ｄ分枝过程,获得了有关过程的渐近性态以及灭 绝概率的一些结果．     

Creating Powerful Learning Environments: Beyond the Classroom

Abstract

Academic Turmoil by Theodore L. Gross. New York: Anchor Press/ Doubleday, 250 pages, $10.95.     

马氏环境中马氏链的Shannon-McMillan-Breiman定理

本文给出了随机环境中的可数状态马氏链的Ｓｈａｎｎｏｎ－ＭｃＭｉｌｌａｎ－Ｂｒｅｉｍａｎ定理,这自然是熟知的有限状态时齐马氏链相应结果的拓广。     

平稳环境中马氏链的不可约性

给出若单链X^→具π-不可约性，则环境空间中的平稳分布π-是遍历的．同时也指出在单链叉的状态空间有限的前提下，该单链是强常返的，从而推广了经典马氏链相应的结论．