Cybernetics and Participation: From Theory to Practice

A combination of recent cybernetic discourse provides guidelines for reconsidering our way of thinking about the relationship between government and the governed. With reference to contemporary understanding of natural biological systems and complexity, it is possible to reformulate a language that has tended to be dominated by notions of competition and survival of the fittest. Instead we can perhaps move toward reconsidering social systems in terms of a more dynamic and equitable understanding of the fit and structural dance of different systems, and postulate that the motor for progress is the coexistence of difference rather than might over right. This paper synthesizes the somewhat different insights of Stafford Beer and the Santiago School of Cognition, and reports on a real-world initiative that sought to instantiate governance as a phenomenon constituted by the governed. Technological developments of the knowledge age are proposed as supporting such democratic initiatives.     

IDSS: Designing to Extend the Cognitive Limits

The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.     

IDSS: Designing to Extend the Cognitive Limits

The paper presents the conceptual and operational basis of the creation of IDSS basedon our recent research experiences.In this paper,an intelligent decision support system,IDSS isdefined as:"any interactive system that is specially desinged to improve the decision making of its     

装备体系需求开发研究：能力-任务匹配方法

针对装备体系需求开发的重点,即作战领域到技术领域的指标映射,提出了能力-任务匹配方法。通过分析装备体系需求指标的结构,建立了依靠功能活动来联系的基于任务要求、能力要求和能力缝隙的装备体系需求数学模型。在此基础上提出通过作战任务分析、功能活动分析、作战能力分析和能力缝隙分析四个阶段实现能力 任务匹配,给出了具体步骤和相应的模型。以“空中封锁”示例说明了方法的可行性。     

矿井优化设计预处理的混合专家系统

介绍了一种用于矿井方案优化设计预处理的混合专家系统——基于神经网络与规则推理的专家系统；阐述了该混合专家系统的基本结构及实现过程，提出输出向量的模糊分类；此外，简要介绍了该系统的实际应用。     

Characteristic Decomposition: From Regular Sets to Normal Sets

Journal of Systems Science and Complexity - In this paper it is shown how to transform a regular triangular set into a normal triangular set by computing the W-characteristic set of their saturated...     

Complex cyber-physical networks: From cybersecurity to security control

Complex cyber-physical network refers to a new generation of complex networks whose normal functioning significantly relies on tight interactions between its physical and cyber components. Many modern critical infrastructures can be appropriately modelled as complex cyber-physical networks. Typical examples of such infrastructures are electrical power grids, WWW, public transportation systems, state financial networks, and the Internet. These critical facilities play important roles in ensuring the stability of society as well as the development of economy. Advances in information and communication technology open opportunities for malicious attackers to launch coordinated attacks on cyber-physical critical facilities in networked infrastructures from any Internet-accessible place. Cybersecurity of complex cyber-physical networks has emerged as a hot topic within this context. In practice, it is also very crucial to understand the interplay between the evolution of underlying network structures and the collective dynamics on these complex networks and consequently to design efficient security control strategies to protect the evolution of these networks. In this paper, cybersecurity of complex cyber-physical networks is first outlined and then some security enhancing techniques, with particular emphasis on safety communications, attack detection and fault-tolerant control, are suggested. Furthermore, a new class of efficient secure control strategies are proposed for guaranteeing the achievement of desirable pinning synchronization behaviors in complex cyber-physical networks against malicious attacks on nodes. The authors hope that this paper motivates to design enhanced security strategies for complex cyber-physical network systems, to realize resilient and secure critical infrastructures.     

Detecting community structure: From parsimony to weighted parsimony

Community detection has attracted a great deal of attention in recent years. A parsimony criterion for detecting this structure means that as minimal as possible number of inserted and deleted edges is needed when we make the network considered become a disjoint union of cliques. However, many small groups of nodes are obtained by directly using this criterion to some networks especially for sparse ones. In this paper we propose a weighted parsimony model in which a weight coefficient is introduced to balance the inserted and deleted edges to ensure the obtained subgraphs to be reasonable communities. Some benchmark testing examples are used to validate the effectiveness of the proposed method. It is interesting that the weight here can be determined only by the topological features of the network. Meanwhile we make some comparison of our model with maximizing modularity Q and modularity density D on some of the benchmark networks, although sometimes too many or a little less numbers of communities are obtained with Q or D, a proper number of communities are detected with the weighted model. All the computational results confirm its capability for community detection for the small or middle size networks.     

Emergence: A Systems Theory’s Challenge to Ethics

The paper reconstructs Niklas Luhmann’s diagnosis of the dysfunctional character of moral communication in the modern society by emphasizing the emergent character of today’s moral problems. In the systems-theoretic literature, emergence means the irreducibility of the properties of the whole to the characteristics of its parts. Two arguments have been advanced. First, the dysfunctional character of moral communication has been traced back to the emergent character of many moral problems. Moral communication has thus been shown to be not inherently dysfunctional, but rather needful of semantic forms that take account of the emergent properties of the economic and other social systems. Second, these properties highlight the moral aspect of the precariousness of system–environment relations as seen by Luhmann. As a moral problem, this precariousness can be resolved through greater sensitivity of social systems to their environment, social and natural alike. Accordingly, the emergent properties of the economic and other social systems can be captured by recasting the concept of responsibility as the individual-level or organizational-level projection of the environmental sensitivity of these systems.     

Singular spectrum analysis: methodology and application to economics data

This paper describes the methodology of singular spectrum analysis (SSA) and demonstrate that it is a powerful method of time series analysis and forecasting, particulary for economic time series. The authors consider the application of SSA to the analysis and forecasting of the Iranian national accounts data as provided by the Central Bank of the Islamic Republic of Iran. This research was in part supported by a grant (No. 88/121230) from Institute for Trade Studies and Research (ITSR), Tehran, Iran.     

Action Research: Its History and Relationship to Scientific Methodology

Scientific Methodology (SM) has long suited those who favour analytical and quantitative research in management. Thus the dilemma between the rigour and relevance of contemporary management research methods is fuelled by action researchers who keep wanting to contrast Action Research (AR) with SM. This paper presents a Western philosophical view on the development of belief systems and theory-based methods over time. It thus links the progressive and cumulative development of SM with the contemporary AR methodology. In doing this it presents a different point of view—that the traditions of SM and AR have much closer relationships than people often give them credit for.     

Reinforcement learning for mobile robot:fromreaction to deliberation

1 .INTRODUCTIONAutonomous mobilerobotics has beena veryi mportant re-searcharea in artificial intelligence and control theory fordecades. Researchers have developed series of methodolo-giesto build mobile robots withself-learning and adaptivecontrol capabilities,rangingfromdeliberative model-basedto purelyreactive paradigms.But nostrongsuccesses havebeen achieved yet . For there are three main difficulties:(1) We cannot programeverything for the robot ,espe-cially in an unknown environmen…     

From Action Research to System in Environments: A Method

This paper describes a breakthrough method for obtaining a quantitative picture of an organization in its environments from qualitative Search Conference data. As such it validates the concept of a system in transaction with its environments, the relevant uncertainty of the current extended social environment with its mixture of ideal seeking and maladaption, and many other OST(E) constructs. The organization is a region of the USDA–Forest Service which used a series of 13 Searches to plan the future of the region. The overall picture produced demonstrates how the method extends the joint purposes of social science to generate further hypotheses about changing systems in today's global social field. It also shows that three beliefs in the social science literature can be dispelled; (1) it is difficult to measure complex phenomena, (2) qualitative and quantitative data are incommensurate, and (3) only a small number of variables can be handled simultaneously.     

粗集在数据开采中的应用

从数据库或数据仓库开采有用的知识，是辅助决策的有效手段，粗集作为一种新的软计算方法，是处理不确定、不完全数据的有效方法，它可以克服其他软计算方法的不足，并且和它们具有较强的亲和力，所以粗集理论得到了广泛的应用，尤其是数据开采领域巳成为研究的热点，论文就粗集在数据开采中的几个重要问题进行论述，包括决策表的约简、不完全决策表的处理，连续值的离散化、基于粗集数据开采的递增算法以及粗集与其他软计算方法的集成等几个前沿问题，同时指出了问题之所在，提出粗集进一步可能的发展方向。