On Quantum Team Games

Recently Liu and Simaan (2004) convex static multi-team classical games have been introduced. Here they are generalized to both nonconvex, dynamic and quantum games. Puu's incomplete information dynamical systems are modified and applied to Cournot team game. The replicator dynamics of the quantum prisoner's dilemma game is also studied.     

Maximum Shannon Entropy, Minimum Fisher Information, and an Elementary Game

We formulate an elementary statistical game which captures the essence of some fundamental quantum experiments such as photon polarization and spin measurement. We explore and compare the significance of the principle of maximum Shannon entropy and the principle of minimum Fisher information in solving such a game. The solution based on the principle of minimum Fisher information coincides with the solution based on an invariance principle, and provides an informational explanation of Malus' law for photon polarization. There is no solution based on the principle of maximum Shannon entropy. The result demonstrates the merits of Fisher information, and the demerits of Shannon entropy, in treating some fundamental quantum problems. It also provides a quantitative example in support of a general philosophy: Nature intends to hide Fisher information, while obeying some simple rules.     

A Genetic Search for Exploiting a Fuzzy Preference Model of Portfolio Problems with Public Projects

When an organization solves a portfolio problem with public projects evaluated by multiple criteria, in which the economic dimension is not essential or not well characterized, the classical methods are not useful. We propose a non-linear preference model developed from normative Value Theory and using fuzzy sets to model some sources of imprecision. This model can be considered as a generalization of the classical approaches. However, the optimization problem is very complex in order to be solved with non-linear programming techniques. Therefore, the model is exploited by an evolutionary algorithm, able to achieve a strong improvement of the quality of solution.     

基于进化人工神经网络的组合系统滤波技术

在组合系统运用Kalman滤波器技术时,准确的系统模型和可靠的观测数据是保证其性能的重要因素,否则将大大降低Kalman滤波器的估计精度,甚至导致滤波器发散.为解决上述Kalman应用中的实际问题,提出了一种新颖的基于进化人工神经网络技术的自适应Kalman滤波器.仿真试验表明该算法可以在系统模型不准确时、甚至外部观测数据短暂中断时,仍能保证Kalman滤波器的性能.     

凸合成模糊对策的模糊稳定集

本建立了凸合成模糊对策的模型，并得到了凸合成模糊对策的模糊稳定集，可由子对策的模糊稳定集表达出来。从而解决了凸合成模糊对策的解的结构问题。     

The Convergence and Stability of Splitting Finite-Difference Schemes for Nonlinear Evolutionary Equations

We consider a splitting finite-difference scheme for an initial-boundary value problem for a two-dimensional nonlinear evolutionary equation. The problem is split into nonlinear and linear parts. The linear part is also split into locally one-dimensional equations. We prove the convergence and stability of the scheme in L ₂ and C norms. Printed in Lietuvos Matematikos Rinkinys, Vol. 45, No. 3, pp. 413–434, July–September, 2005.     

逆（反）对策问题与“奇门遁甲”预测理论（术）

本文首先提出逆（反）对策这一新问题，给出了数学模型；探讨了“奇门遁甲”预测理论（术）中的数学问题；通过系统分析“专门遁甲”预测过程，可知它的预测过程隐含着一个特殊的逆（反）对策问题；最后指出逆（反）对策问题的广泛存在并给出案例分析．     

Action learning versus strategy learning

This article seeks to ascertain whether the strategy‐learning model of Hanaki, Sethi, Erev, and Peterhansl (2003) better accounts for observed behavior than do the various action‐learning models. It does so by measuring the goodness‐of‐fit of the models' predictions against published experimental results for such games as Coordination, Prisoner's Dilemma, and Chicken. The fit is measured via the mean squared deviation (MSD) between the observed behavior and the one predicted by the model. The results show that, for Chicken, the strategy‐learning model fits the observed data much better than do the action‐learning models. The best action‐learning model, on the other hand, fits the observed data well in Coordination. Overall, the strength of the strategy‐learning model is best shown in games where alternations between the two stage‐game Nash equilibria are often observed in the laboratory experiments. © 2004 Wiley Periodicals, Inc. Complexity 9: 41–50, 2004     

基于演化博弈的武器装备研制合同定价模型研究

针对合同的动态性，提出利用基于演化博弈建立定价模型。考虑到决策群体中个体的认识误差，对所建立的定价模型进行修正，建立带偏离的定价模型并分析了偏离对均衡解的影响。最后将以上模型应用实例进行比较分析。     

基于模糊方法的多人合作对策的研究

多人合作对策模型中联盟的收入和总体的收入常常出现相互矛盾的情况 ,此时核是空集 .由于不存在核 ,无法用 Nash-Harsanyi谈判模型求解 .采用模糊数学方法 ,调整模型中线性约束的右端系数 ,使核在一定程度上是非空集合 ,得到模糊意义下的 Nash平衡解 .该方法一定程度上解决了各联盟收入与总体收入的矛盾 .最后通过一个算例说明该方法的可行性 .