A search game taking account of attributes of searching resources

This article deals with a two‐person zero‐sum game called a search allocation game (SAG), in which a searcher and a target participate as players. The searcher distributes his searching resources in a search space to detect the target. The effect of resources lasts a certain period of time and extends to some areas at a distance from the resources' dropped points. On the other hand, the target moves around in the search space to evade the searcher. In the history of search games, there has been little research covering the durability and reachability of searching resources. This article proposes two linear programming formulations to solve the SAG with durable and reachable resources, and at the same time provide an optimal strategy of distributing searching resources for the searcher and an optimal moving strategy for the target. Using examples, we will analyze the influences of two attributes of resources on optimal strategies. © 2007 Wiley Periodicals, Inc. Naval Research Logistics 2008     

浅析国家审计免疫系统论

“国家审计免疫系统论”是新时期从战略的高度对审计本质所作出的精辟、简洁、鲜明的表述,体现了时代精神,揭示了中国审计的根本性质就是保护与防御。这一理论具有创新精神,它把审计上升到了国家安全的高度,其目的是为国家“强身健体”。正确认识“审计免疫系统论”的内涵、本质、功能,对于指导我国审计理论和审计工作发展具有重要的理论意义和实践意义。     

线性系统的鲁棒容错控制设计方法

考虑了线性故障系统的鲁棒容错控制问题。利用状态反馈特征结构配置参数化结果,提出了一种鲁棒容错控制设计方法。该方法将故障系统的鲁棒容错控制问题转化为含有约束的最小化问题。数值算例及其仿真结果验证了所设计方法的简单性和有效性。     

往返搜索发现概率仿真分析与应用

往返搜索是一种最常见的搜索样式,其搜索效能与搜索宽度、发现距离、搜索速度、突破速度等因素密切相关。在建立往返搜索行动模型的基础上,通过仿真实验得到耕耘数据,进而通过数据分析和处理得到往返搜索发现概率的经验公式。应用经验公式并结合声纳探测模型,对多搜索艇分段封锁搜索案例进行了优化研究。     

航空发动机自适应模拟退火遗传算法建模

以阶跃输入响应进行模型的检验,提出了航空发动机状态模型的建立方法:在抽功法所建立的状态空间模型的基础上,利用自适应模拟退火遗传算法对A、C矩阵元素进行寻优,解决了状态空间模型的响应与非线性模型不能够很好吻合的难题。仿真表明,得到的状态空间模型无论是动态过程还是稳态过程都能取得较高的建模精度,为航空发动机分布式控制的研究奠定了强有力的基础。     

基于多Agent无人机协同侦察任务规划模型

建立了多无人机协同侦察任务规划模型,在考虑侦察时间间隔约束和目标载荷需求基础上,给出了位于不同基地的无人机优化部署和调度策略,并提出了基于多Agent的优化搜索仿真算法,利用Matlab实现了无人机优化配置和任务规划模型,得出了无人机优化配置和任务规划方案,最后分析了模型算法存在的某些不足,提出了模型改进的方向。     

多帧高斯混合概率假设密度的多目标跟踪算法

针对低检测概率下多目标跟踪时,概率假设密度滤波器难以正确估计当前目标个数以及目标状态问题,提出一种基于多帧融合的高斯混合概率假设密度滤波算法。根据不同时刻目标权值构造目标多帧权值记录集及目标状态抽取标志。当某些时刻目标被漏检时,依据目标状态抽取标志,并结合目标多帧权值记录集中权值信息估计丢失目标的状态。仿真实验表明,算法有效地提高了低检测概率下现有相关算法的目标状态和数目估计精度。     

Technical note: Find a hidden “treasure”

This paper deals with a two searchers game and it investigates the problem of how the possibility of finding a hidden object simultaneously by players influences their behavior. Namely, we consider the following two‐sided allocation non‐zero‐sum game on an integer interval [1,n]. Two teams (Player 1 and 2) want to find an immobile object (say, a treasure) hidden at one of n points. Each point i ∈ [1,n] is characterized by a detection parameter λ_i (μ_i) for Player 1 (Player 2) such that p_i(1 ? exp(?λ_ix_i)) (p_i(1 ? exp(?μ_iy_i))) is the probability that Player 1 (Player 2) discovers the hidden object with amount of search effort x_i (y_i) applied at point i where p_i ∈ (0,1) is the probability that the object is hidden at point i. Player 1 (Player 2) undertakes the search by allocating the total amount of effort X(Y). The payoff for Player 1 (Player 2) is 1 if he detects the object but his opponent does not. If both players detect the object they can share it proportionally and even can pay some share to an umpire who takes care that the players do not cheat each other, namely Player 1 gets q₁ and Player 2 gets q₂ where q₁ + q₂ ≤ 1. The Nash equilibrium of this game is found and numerical examples are given. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Constrained minimax optimization of continuous search efforts for the detection of a stationary target

Analytical resolution of search theory problems, as formalized by B.O. Koopman, may be applied with some model extension to various resource management issues. However, a fundamental prerequisite is the knowledge of the prior target density. Though this assumption has the definite advantage of simplicity, its drawback is clearly that target reactivity is not taken into account. As a preliminary step towards reactive target study stands the problem of resource planning under a min–max game context. This paper is related to Nakai's work about the game planning of resources for the detection of a stationary target. However, this initial problem is extended by adding new and more general constraints, allowing a more realistic modeling of the target and searcher behaviors. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

集群搜索对策理论在搜索-规避对抗中的应用

使用对策论的观点和方法 ,结合搜索论的知识 ,建立了一类搜索 -规避对抗对策模型 .对模型的结论做了系统分析 ,考虑了对策双方的最优策略及使用 .