常量与变量——谈《拿破仑——全面战争》系统设计的进化

这真是资料片？——诚意之作 早在《拿破仑——全面战争》（以下简称NTW）宣布之初,Creative Assembly（以下简称A）就力图展示这样一个信息：NTW是《帝国——全面战争》（以下简称ETW）的续作。     

自然计算在九大高新技术领域的应用研究

在上海市重点发展的九大高新技术领域,对自然计算的内涵及应用进行了简介,综述了自然计算内涵的各类技术,在国内外九大高新技术领域的应用现状。通过应用现状对比,分析国内外应用的差距与优势,提出相应的改进意见,最后对自然计算进一步的应用前景进行了总结与展望。     

系统详解

久违的“《前线任务》系列”终于迎来了最新作——《前线任务 进化》。正如其名,本作可真谓是大刀阔斧的进化,一改系列以往的战略类游戏类型而变为了动作射击游戏,更是加入了多人联机对战模式。     

高维进化策略调整神经网络结构和参数

提出一种基于佳点集原理的进化策略用于神经网络结构和参数的调整.为了克服正交设计法的一些不足来处理高维最优化问题,本文采用分步交叉框架,将佳点集技术引入实数域交叉算子增强高维空间的搜索能力.前馈神经网络的隐含节点与连接边数从小逐步递增直至学习效果足够好.通过调整能得到一个部分连接的前馈网络,减少了网络实现的耗费.最后,佳点集进化策略有效应用于生成预测太阳黑子的演化神经网络.实验结果证明了新方法的有效性.     

Pollard p-1因子分解的DNA计算机算法

如何有效地对大整数进行因子分解是数学上的一个难题.给出了基于分子生物技术的因子分解问题的DNA计算机算法.算法以Pollard p-1算法为基础,利用DNA分子生物操作完成加、减、乘、除运算,实现平方-乘以及欧几里德算法,产生并得到最终解.基于分子生物学的实验表明,该算法是可行和有效的.     

基于迁徙差分进化算法集成的模体识别

为了克服微分进化的局部收敛问题,通过模拟游牧民族的迁徙机制,提出一种迁徙策略,将其与差分进化算法相结合,得到一种迁徙差分进化算法新范式,利用集成技术,发挥各种差分进化算法的优点,提高算法的全局搜索能力。通过生物序列模体识别实验,验证了该算法的有效性。     

Stability and control of nonlinear systems described by retarded functional equations: a review of recent results

This paper reports on recent results in a series of the work of the authors on the stability and nonlinear control for general dynamical systems described by retarded functional differential and difference equations. Both internal and external stability properties are studied. The corresponding Lyapunov and Razuminkhin characterizations for input-to-state and input-to-output stabilities are proposed. Necessary and sufficient Lyapunov-like conditions are derived for robust nonlinear stabilization. In particular, an explicit controller design procedure is developed for a new class of nonlinear time-delay systems. Lastly, sufficient assumptions, including a small-gain condition, are presented for guaranteeing the input-to-output stability of coupled systems comprised of retarded functional differential and difference equations.     

Statistical learning makes the hybridization of particle swarm and differential evolution more efficient—A novel hybrid optimizer

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality. Supported by the National Natural Science Foundation of China (Grant No. 60374069), and the Foundation of the Key Laboratory of Complex Systems and Intelligent Science, Institute of Automation, Chinese Academy of Sciences (Grant No. 20060104)     

极客进化简史：从盖茨到谷歌创始人

在智能手机、社交网站等高科技必需之物问世以前,极客（Geek,亦称奇客）带有一点儿贬义,通常是指那些性格古怪但大多智力超群、善于钻研的人。白衬衫、黑领带和牛角框眼镜是他们的“标配”。一开始,他们并未像现在这样受到主流社会的欢迎。不过,经过数十年的发展,极客已摆脱了旧式的装扮,展现出新的面貌,在商界和社会上更被人们所接受。     

前线任务 进化

2171年,人类开始向着宇宙这片广阔而又未知的空间移民,地球上的各个列强国家分别开始建设地球轨道电梯,随着宇宙移民计划的迫近,各国相继以“宇宙移民”为理由扩充军备,在海、陆、空三方面不断发生流血冲突的如今,人类也面临着宇宙战争的威胁。