Equilibrium in a Network Game with Production and Knowledge Externalities

In each node of a network, economy is described by the simple two-period Romer’s model of endogenous growth with production and knowledge externalities. The sum of knowledge levels in the neighbor nodes causes an externality in the production of each node of the network. The game equilibrium in the network is investigated. The agents’ solutions depending on the size of externality are obtained. The uniqueness of inner equilibrium is proved. The role of passive agents in network formation is studied; in particular, the possibilities of adding a passive agent to a regular network, and also of joining of regular networks through nodes with passive agents. It is shown that the sum of knowledge levels in all the nodes decreases under adding of a new link.     

广义Nash平衡点和切换控制在对策论中的应用

通过把平衡点和决策者的动机耦合的方法,提出了广义纳什平衡点这一新概念.决策者的动机通常有两类：一是最大化自己的利益,另一则是最大化对手的利益.如果每一个决策者的动机都是第一类,一个理性的群体就会形成,整个系统最终会达到第一类平衡点（也就是经典的纳什平衡点）.如果每一个决策者的动机都是第二类,一个有智慧的群体就会形成,整个系统最终会达到第二类平衡点.同时,切换控制被用来帮助决策者确定他们的动机.     

Individual Stability of Coalition Structures in Three-Person Games

Automation and Remote Control - Cooperative games with coalition structures are considered, and a principle of coalition structure individual stability with respect to some cooperative solution...     

A Differential Game Model of Oligopoly

Most of the literature on oligopoly deals with profit-maximizing firms engaging in “static” repetitive games. As the number of firms increases, the Nash-equilibrium strategy for each Cournot oligopolist converges to the competitive solution. In a two-person, zero-sum differential game model of duopoly [1] we introduced dynamic elements and explored alternative entrepreneurial goals. The duopolists endeavor to outsell each other subject to a no-loss constraint; the saturation of present markets by past sales and the impact on future goodwill by current advertisement are handled through “state variables.” The differential game formulation [1, 2] offers two advantages: (a) near perfect information leads to frequent existence of pure strategy equilibria and (b) the use of optimal control theory facilitates the characterization of the time structure of an equilibrium. However, the two-person, zero-sum framework is too restrictive while a general theory for solving n-person, non-zero sum differential games has still not been developed [3, 4].     

Numerical Simulation of Non-cooperative and Cooperative Equilibrium Solutions for a Stochastic Government Debt Stabilization Game

Computational Economics - In this article, we consider the impact uncertainty has on policies and realization of targets aimed at the stabilization of government debt. The problem is motivated by...     

Coordination of the Equilibrium Controls in Hierarchic Systems by Game Theory Methods

In connection with a wide prevalence of hierarchic structure systems in very different spheres of activity (industrial and economic, animate nature, etc.) and considerable difficulties associated with their analysis, the problem of the unit, the “AND” problem according to the Bertalanffy playful formulation, has become of paramount importance. At the same time the integration into the unit is achieved by means of coordination. It is the coordination (in particular, the coordination principles) that permits the revealing of mechanisms for achieving integration in hierarchic control systems [8].     

基于模糊微分对策多机空战组内协同的U解

鉴于协商微分对策多具有强非线性和不确定性特点,为避免非线性问题等带来求解上的困难和能处理不确定信息,基于T-S模糊微分对策的思想,对非线性的基于Utilitarian解(简称U解)的协商微分对策的状态方程和性能分别进行了模糊化和二次型化,构造出面向U解的协商微分对策的模糊线性化模型,研究了协商U解模型中加权系数的确定,并进一步探讨了在模糊线性协商微分对策系统下相应于U解的控制器的设计方法.研究工作和仿真结果可以说明,相对于Nash协商解,协商理论的U解更能反映整体效果,更易于推广.     

Pareto group structure in a multicriteria optimization problem

A multicriteria choice problem is considered. It is proposed to solve this problem by requiring the solution to be invariant under a certain group of transformations. Groups of transformations of a linear space that preserve the Pareto order in this space are investigated. The maximum group of such transformations is calculated up to group isomorphism. The most interesting discrete and continuous subgroups of the Pareto group are considered.     

Numerical Construction of Stackelberg Solutions in a Linear Positional Differential Game Based on the Method of Polyhedra

We consider the problem of constructing approximate Stackelberg solutions in a linear non-zero-sum positional differential game of two players with terminal payoffs and player controls chosen on convex polyhedra. A formalization of player strategies and motions generated by them is based on the formalization and results of the theory of zero-sum positional differential games developed by N.N. Krasovskii and his scientific school. The problem of finding a Stackelberg solution reduces to solving nonstandard optimal control problems. We propose an approach based on operations with convex polyhedra.     

自适应低秩稀疏分解在运动目标检测中的应用

针对视频处理中运动目标的精确检测这一问题,提出了一种自适应的低秩稀疏分解算法。该算法首先用背景模型与待求解的帧向量构建增广矩阵,然后使用鲁棒的主成分分析(robust principal component analysis,RPCA)对降维后的增广矩阵进行低秩稀疏分解,分离出的低秩部分和稀疏噪声分别对应于视频帧的背景和运动前景,然后使用增量奇异值分解方法用当前得到的背景向量更新背景模型。实验结果表明,该算法能更好地处理光线变化、背景运动等复杂场景,并有效降低算法的延迟和内存的占用。     

Pareto Optimal Decentralized Control of a Rotor in Electromagnetic Bearings

Journal of Computer and Systems Sciences International - The problem of the optimal stabilization of a vertical rigid rotor rotating in two electromagnetic bearings is considered. A quantitative...     

Fast computation of equispaced Pareto manifolds and Pareto fronts for multiobjective optimization problems

In this paper, we consider the problem of generating a well sampled discrete representation of the Pareto manifold or the Pareto front corresponding to the equilibrium points of a multi-objective optimization problem. We show how the introduction of simple additional constraints into a continuation procedure produces equispaced points in either of those two sets. Moreover, we describe in detail a novel algorithm for global continuation that requires two orders of magnitude less function evaluations than evolutionary algorithms commonly used to solve this problem. The performance of the methods is demonstrated on problems from the current literature.     

Estimating the Parameters of a Tapered Pareto Distribution

Automation and Remote Control - The article deals with the problem of estimating the parameters of a tapered Pareto distribution. Using the moment method, we obtain new estimates depending on an...     

Optimal Navigation for a Differential Drive Disc Robot: A Game Against the Polygonal Environment

This paper considers the problem of globally optimal navigation with respect to minimizing Euclidean distance traveled by a disc-shaped, differential-drive robot (DDR) to reach a landmark. The robot is equipped with a gap sensor, which indicates depth discontinuities and allows the robot to move toward them. In this work we assume that a topological representation of the environment called GNT has already been built, and that the landmark has been encoded in the GNT. A motion strategy is presented that optimally navigates the robot to any landmark in the environment, without the need of using a previously known geometric map of the environment. To our knowledge this is the first time that the shortest path for a DDR (underactuated system) is found in the presence of obstacle constraints without knowing the complete geometric representation of the environment. The robot’s planner or navigation strategy is modeled as a Moore Finite State Machine (FSM). This FSM includes a sensor-feedback motion policy. The motion policy is based on the paradigm of avoiding the state estimation to carry out two consecutive mappings, that is, from observation to state and then from state to control, but instead of that, there is a direct mapping from observation to control. Optimality is proved and the method is illustrated in simulation.     

游戏引擎在游戏开发中的应用

我们常常会碰见“引擎“(Engine)这个单词,引擎在游戏中究竟起着什么样的作用?怎样实现?以及它在游戏开发中处于什么地位?本文做了比较详细的介绍.     

游戏引擎在游戏开发中的应用

我们常常会碰见“引擎”（Engine）这个单词,引擎在游戏中究竟起着什么样的作用？怎样实现？以及它在游戏开发中处于什么地位？本文做了比较详细的介绍。     

Empirical Bayes estimation of the scale parameter in a Pareto distribution

Let f(xθ) = αθ^αx^−(α+1)I(x>θ) be the pdf of a Pareto distribution with known shape parameter α>0, and unknown scale parameter θ. Let {(X_i, θ_i)} be a sequence of independent random pairs, where X_i's are independent with pdf f(xα_i), and θ_i are iid according to an unknown distribution G in a class of distributions whose supports are included in an interval (0, m), where m is a positive finite number. Under some assumption on the class and squared error loss, at (n + 1)th stage we construct a sequence of empirical Bayes estimators of θ_n+1 based on the past n independent observations X₁,…, X_n and the present observation X_n+1. This empirical Bayes estimator is shown to be asymptotically optimal with rate of convergence O(n^−1/2). It is also exhibited that this convergence rate cannot be improved beyond n^−1/2 for the priors in class .     

A multi-objective selection procedure of determining a Pareto set

Ranking and selection (R&S) procedures have been widely studied and applied in determining the required sample size (i.e., the number of replications or batches) for selecting the best system or a subset containing the best system from a set of k alternatives. Most of the studies in the R&S have focused on a single measure of system performance. In many practical situations, however, we need to select systems based on multiple criteria. A solution is called Pareto optimal if there exists no other solution which is better in all criteria. This paper discusses extending a R&S procedure to select a Pareto set containing non-dominated systems. Computational results show that the proposed procedures are effective in obtaining non-dominated systems.     

面向对象的数据模型设计方法的研究与实现

应用程序处理的数据大部分来源于数据库,数据库中的数据与应用程序交互的数据模型接口存在差异,如何利用更适合应用的＂概念模型＂来处理数据库中的数据,简化应用程序的设计和调用,是软件设计师和数据架构师必须合作解决的问题。利用概念模型的方法将数据在存储和调用过程中的复杂问题简易化,从而为大型应用程序的数据处理提供一种方法。     

Pareto frontier for simultaneous structural and manufacturing optimization of a composite part

Optimized design of composite structures requires simultaneous optimization of structural performance and manufacturing process. Such a challenge calls for a multi-objective optimization. Here, a generating multi-objective optimization method called normalized normal constraint method, which attains a set of optimal solutions and allows the designer to explore design alternatives before making the final decision, is coupled with a local-global search called constrained globalized bounded Nelder–Mead method. The proposed approach is applied to the design of a Z-shaped composite bracket for optimization of structural and manufacturing objectives. Comparison of the results with non-dominated sorting genetic algorithm (NSGA-II) shows that when only a small number of function evaluations are possible and a few Pareto optima are desired, the proposed method outperforms NSGA-II in terms of convergence to the true Pareto frontier. The results are validated by an enumeration search and by exploring the neighbourhood of the final solutions.