Robust eigenstructure assignment combining time- and frequency-domain performance specifications

This paper is concerned with robust eigenstructure assignment for multivariable systems. It combines time-domain performance specifications provided by eigenstructure assignment and robust performance specifications in the frequency domain considered by H^∞ control to realize joint optimal robust control design. A unified parametric solution for state-feedback eigenstructure assignment is derived for both the case where the sets of closed- and open-loop eigenvalues do not intersect and the case where these sets do intersect. This is based on a set of free parameters. All complex operations are converted into the real field so that the algorithm which is developed for the controller design can be easily implemented on computers. It uses a robustness index defined in the frequency domain as the cost function to be optimized. The analytical gradient calculation of the cost function with respect to the free parameters is given. Using gradient-based optimization, the robustness index is minimized by making full use of the freedom provided by eigenstructure assignment. © 1998 John Wiley & Sons, Ltd.     

Insensitive and robust control design via output feedback eigenstructure assignment

Insensitive and robust control design using output‐feedback eigenstructure assignment for linear multivariable systems is considered in this paper. A parametric expression of closed‐loop eigenvectors and generalized eigenvectors is developed. It can cope with the case where the closed‐loop eigenvalues are multiple and/or the same as the open‐loop ones so that the system to be designed can be uncontrollable and/or unobservable. The controller designed via output‐feedback eigenstructure assignment is expressed by proposed parameter vectors. The freedom provided by output‐feedback eigenstructure assignment is used to optimize some performance functions which are used to measure the sensitivity of the closed‐loop matrix and the robustness of the closed‐loop system. Copyright © 2000 John Wiley & Sons, Ltd.     

重复囚徒困境的学习和响应模型

囚徒困境问题是博弈论的一个重要范例,对此的研究涉及经济学、社会学、生物学等广泛领域。Axelrod R在文献[1]中从进化的角度研究和探讨了经典囚徒困境的一个扩展--重复囚徒困境。这种博弈要求参与者反复进行囚徒困境的博弈,并且可以记住他们的对抗历史。Axelrod还组织了两次重复囚徒困境的计算机竞赛,最终胜出的都是简单的＂以
牙还牙＂策略[2]。这之后有不少学者试图找到可以击败它的策略,都未能取得显著成功。本文提出了一种学习和响应的理论模型,实际中的许多重复囚徒困境的策略都可以纳入这一模型中。我们分析了实现这一模型的难点和复杂度,同时给出了一种基于树结构的实现方式,并在实验中把它和“以牙还牙”作比较。实验以及分析表明,策略在竞赛中表现的优劣主要取决于如何利用一些启发式规则来权衡学习代价和博弈的总利益,以及在此基础上如何抽取对手的关键信息。     

The effects of viscosity in choice and refusal IPD environments

An objective of multi-agent systems is to build robust intelligent systems capable of existing in complex environments. These systems are often characterised as being uncertain and open to change which make such systems far more difficult to design and understand. Some of this uncertainty and change occurs in open agent environments where agents can freely enter and exit the system. In this paper we will examine this form of population change in a game theoretic setting. These simulations involve studying population change through a number of alternative viscosity models. The simulations will examine two possible trust models. All our simulations will use a simple choice and refusal game environment within which agents may freely choose with which of their peers to interact.     

The emergence of cooperation in the random asynchronous prisoner’s dilemma

The iterated prisoners dilemma (IPD) is a simple model for the study of the emergence of cooperative behavior in populations of selfish individuals. In this work, we challenge the assumption that players move in synchrony, and develop a general Markovian model that allows the study of a wide spectrum of scenarios. Simulations show that the relative timing of player moves, and the reward for mutual cooperation, influences the strategy that eventually dominates the final population. For a synchronous environment, reciprocal behavior appears to be the key to the evolution of cooperation, while in an asynchronous environment, guarded generosity may be a route to the evolution of cooperation.     

PRISONER'S DILEMMA REVISITED: A NEW STRATEGY BASED ON THE GENERAL SYSTEM PROBLEM SOLVING FRAMEWORK

In this paper, the famous Prisoner's Dilemma Problem is reexamined by using the methodology of the General System Problem Solving (GSPS) Framework. It is shown that this framework provides us with a powerful means to take into account the secondary effects that were ignored by previous strategies. In a classroom contest, the new strategy proved far superior to previously employed techniques.     

Improved robust stability criteria and design of robust stabilizing controller for uncertain linear time‐delay systems

In this paper, an improved linear matrix inequality (LMI)‐based robust delay‐dependent stability test is introduced to ensure a larger upper bound for time‐varying delays affecting the state vector of an uncertain continuous‐time system with norm‐bounded‐type uncertainties. A quasi‐full‐size Lyapunov–Krasovskii functional is chosen and free‐weighting matrix approach is employed. Less restrictive sufficient conditions are derived for robust stability of time‐varying delay systems with norm‐bounded‐type uncertainties. Moreover, the investigation of the stabilization problem with memoryless state‐feedback control is presented such that the stabilizability criteria are obtained in terms of matrix inequalities, which can be solved via utilizing a cone complementarity minimization algorithm. Finally, the problem of output feedback stabilization for square systems is also taken into consideration. The output feedback stabilizability criteria are derived in the form of linear matrix inequalities, which are convex and can be easily solved using interior point algorithms. A plenty of numerical examples are presented indicating that the proposed stability and stabilization methods effectively improve the existing results. Copyright © 2006 John Wiley & Sons, Ltd.     

基于社交信任和标签偏好的景点推荐方法

针对现有的景点推荐算法在处理用户关系时忽视了用户隐性信任和信任传递问题,以及当用户处于新城市时由于缺乏用户历史记录无法做出准确推荐的情况,本文提出一种综合用户信任关系和标签偏好的个性化景点推荐方法.在仅仅考虑用户相似度时推荐质量差的情况下引入信任度,通过挖掘用户隐性信任关系解决了现有研究在直接信任难以获取时无法做出推荐的情况,有效缓解了数据稀疏性和冷启动问题.同时在用户兴趣分析过程中将景点和标签的关系扩展到了用户、景点和标签三者的相互关系,把用户的兴趣偏好分解成对不同景点标签的长期偏好,有效地缓解了缺乏用户历史游览记录时推荐质量不佳的问题.通过在Flickr网站上收集的数据进行实验验证,结果表明本文提出的混合推荐算法有效地提高了推荐精度,在一定程度上缓解了冷启动和新城市问题.     

A new divergence measure for basic probability assignment and its applications in extremely uncertain environments

Information fusion under extremely uncertain environments is an important issue in pattern classification and decision-making problems. The Dempster-Shafer evidence theory (D-S theory) is more and more extensively applied in dealing with uncertain information. However, the results contrary to common sense are often obtained when combining different evidence using Dempster's combination rule. How to measure the difference between different evidence is still an open issue. In this paper, a new divergence is proposed based on the Kullback-Leibler divergence to measure the difference between different basic probability assignments (BPAs). Numerical examples are used to illustrate the computational process of the proposed divergence. Then, the similarity for different BPAs is also defined based on the proposed divergence. The basic knowledge about pattern recognition is introduced, and a new classification algorithm is presented using the proposed divergence and similarity under extremely uncertain environments. The effectiveness of the classification algorithm is illustrated by a small example handling robot sensing. The proposed method is motivated by the urgent need to develop intelligent systems, such as sensor-based data fusion manipulators, which are required to work in complicated, extremely uncertain environments. Sensory data satisfy the conditions (1) fragmentary and (2) collected from multiple levels of resolution.     

Further results on delay‐dependent absolute and robust stability for time‐delay Lur'e system

In this paper, together with two improved Lyapunov–Krasovskii functionals, several novel sufficient conditions are derived to guarantee two kinds of time‐delay Lur'e system to be absolutely and robustly stable, in which the linear fractional uncertainties are involved, and both time‐delay and its variation rate can be fully utilized. Through using the combined convex technique, some previously ignored terms can be reconsidered when estimating the triple integral Lyapunov–Krasovskii functional terms’ derivative, and the criteria are presented in terms of LMIs, in which its solvability heavily depends on the information of addressed systems. Finally, the comparing results in the numerical examples demonstrate our idea can reduce the conservatism more efficiently than some present ones. Copyright © 2013 John Wiley & Sons, Ltd.     

Visual quality recognition of nonwovens using generalized Gaussian density model and robust Bayesian neural network

This work is dedicated to develop an algorithm for the visual quality recognition of nonwoven materials, in which image analysis and neural network are involved in feature extraction and pattern recognition stage, respectively. During the feature extraction stage, each image is decomposed into four levels using the 9-7 bi-orthogonal wavelet base. Then the wavelet coefficients in each subband are independently modeled by the generalized Gaussian density (GGD) model to calculate the scale and shape parameters with maximum likelihood (ML) estimator as texture features. While for the recognition stage, the robust Bayesian neural network is employed to classify the 625 nonwoven samples into five visual quality grades, i.e., 125 samples for each grade. Finally, we carry out the outlier detection of the training set using the outlier probability and select the most suitable model structure and parameters from 40 Bayesian neural networks using the Occam's razor. When 18 relevant textural features are extracted for each sample based on the GGD model, the average recognition accuracy of the test set arranges from 88% to 98.4% according to the different number of the hidden neurons in the Bayesian neural network.     

基于众筹预售和众包生产的两阶段最优定价机制

为实现农产品产销供应链中按需生产,供需平衡的同时,提高电商平台的期望收益。分析了电商平台整个产销供应链的问题模型,提出一种基于电子商务平台众筹预售和众包生产的产销模式。基于迈尔森最优拍卖理论设计了众筹预售和众包分配的两阶段最优拍卖定价机制,能够在保证参与用户诚实报价的基础上,同时最大化电商平台的期望收益。实验结果表明,对比传统的先到先服务算法（FCFS）,平均收益在需求数量区间为均匀分布时至少增加了5%,为指数分布时至少增加了18%,且至少能达到假设用户诚实报价下的最优利润（OP）收益的50%。     

Maximum cut‐clique problem: ILS heuristics and a data analysis application

This paper focuses on iterated local search heuristics for the maximum cut‐clique (MCC, or clique neighborhood) problem. Given an undirected graph G = (V,E) and a clique C of G, the cut‐clique is the set of edges running between C and V\C, establishing the cut (C,V\C). The MCC in G is to find a clique with the largest number of edges in the neighborhood of the clique, also known as the maximum edge‐neighborhood clique. This problem has been recently introduced in the literature together with a number of applications, namely, in cell biology instances. However, it has only been addressed so far by exact methods. In this paper, we introduce the first approximate algorithms for tackling the MCC problem, compare the results with the exact methodologies, and explore a new application within marketing analysis, which provide a new alternative perspective for mining market basket problems.     

Joint influence of online store attributes and offline operations on performance of multichannel retailers

This study examines the synergistic interchange between online and offline operations. To this end, this study proposed a multichannel performance model integrating Herzberg's (Herzberg 1966 Herzberg, F. 1966. Work and the nature of man, Cleveland, OH: World Publishing.  [Google Scholar]: Work and the Nature of Man, World Publishing, Cleveland, OH) motivation-hygiene theory and Thorndike's (Thorndike 1920 Thorndike, E. L. 1920. A constant error in psychological ratings. Journal of Applied Psychology, 4: 25–29. [Crossref] , [Google Scholar]: J. Appl. Psychol., 4, 25 – 29) halo effect, and empirically tested it. The essence of the model was that e-satisfaction is formed by a varying influence of online (basic and marketing-related attributes) and offline (firm reputation, consumer offline channel use, and consumer offline satisfaction) factors, which then increases e-loyalty. Analyses on a sample of 203 multichannel consumers revealed that, in general, the hypothetical paths were significant except in two cases. In a multichannel's online operation, marketing-related online attributes (e.g. merchandising) exerted significant influence on e-satisfaction, but basic attributes (e.g. security) did not. In a multichannel's offline operation, firm reputation and consumer offline satisfaction contributed to increasing e-satisfaction. Both firm reputation and consumer offline channel use increased consumer offline satisfaction, which in turn increased online satisfaction. However, consumer offline loyalty did not transfer to online loyalty. Theoretical and managerial implications were suggested based on findings.     

公平理性委托计算协议

传统委托计算的验证过程计算和通信开销较高,且参与者要么诚实,要么邪恶;理性委托计算是引入理性参与者,通过效用函数来保障计算结果的可靠性.本文首先在委托计算中引入博弈论,给出了唯一稳定均衡解.其次,基于比特币和Micali-Rabin的随机向量表示技术,设计一种新的理性委托计算协议.针对协议的公平性问题,参与双方分别提交特殊构造的比特币押金,保障参与者双方的利益;针对验证复杂问题,运用Micali-Rabin的随机向量表示技术,验证过程简单高效,且不会泄漏关于计算结果的任何信息.最后,安全性和性能分析结果表明,该协议不但解决了传统委托计算的验证复杂问题,同时保证了诚实者的利益.