Expert discovery and knowledge mining in complex multi-agent systems

Complex problem solving requires diverse expertise and multiple techniques. In order to solve such problems, complex multi-agent systems that include both of human experts and autonomous agents are required in many application domains. Most complex multi-agent systems work in open domains and include various heterogeneous agents. Due to the heterogeneity of agents and dynamic features of working environments, expertise and capabilities of agents might not be well estimated and presented in these systems. Therefore, how to discover useful knowledge from human and autonomous experts, make more accurate estimation for experts＇ capabilities and find out suitable expert（s） to solve incoming problems （＂Expert Mining＂） are important research issues in the area of multi-agent system. In this paper, we introduce an ontology-based approach for knowledge and expert mining in hybrid multi-agent systems. In this research, ontologies are hired to describe knowledge of the system. Knowledge and expert mining processes are executed as the system handles incoming problems. In this approach, we embed more self-learning and self-adjusting abilities in multi-agent systems, so as to help in discovering knowledge of heterogeneous experts of multi-agent systems.     

An Information Analysis Decision System

In recent years, we are increasingly coping with macro, complex and large-scale system in whichinformations twist together. It is a worthwhile research to develop general computer-aided meth-od for decision-making on the basis of processing, analysing and deducing from the informationobtained.     

ON INTEGRATION AND ADAPTATION IN COMPLEX SERVICE SYSTEMS

The services sector employs a large and growing proportion of workers in the industrialized nations, and it is increasingly dependent on information and communication technologies. While the interdependences, similarities and complementarities of manufacturing and services are significant, there are considerable differences between goods and services, including the shift in focus from mass production to mass customization （whereby a service is produced and delivered in response to a customer＇s stated or imputed needs）. In general, services can be considered to be knowledge-intensive agents or components which work together as providers and consumers to create or co-produce value. Like manufacturing systems, an efficient service system must be an integrated system of systems, leading to greater connectivity and interdependence. Integration must occur over the physical, temporal, organizational and functional dimensions, and must include methods concerned with the component, the management, and the system. Moreover, an effective service system must also be an adaptable system, leading to greater value and responsiveness. Adaptation must occur over the dimensions of monitoring, feedback, cybernetics and learning, and must include methods concerned with space, time, and system. In sum, service systems are indeed complex, especially due to the uncertainties associated with the human-centered aspects of such systems. Moreover, the system complexities can only be dealt with methods that enhance system integration and adaptation. The paper concludes with several insights, including a plea to shift the current misplaced focus on developing a science or discipline for services to further developing a systems engineering approach to services, an approach based on the integration and adaptation of a host of sciences or disciplines （e.g., physics, mathematics, statistics, psychology, sociology, etc.）. In fact, what is required is a services-related transdisciplinary - beyond a single disciplinary - ontology or taxon     

ADAPTIVE SYSTEMS THEORY： SOME BASIC CONCEPTS, METHODS AND RESULTS

The adaptive systems theory to be presented in this paper consists of two closely related parts: adaptive estimation (or filtering, prediction) and adaptive control of dynamical systems. Both adaptive estimation and control are nonlinear mappings of the on-line observed signals of dynamical systems, where the main features are the uncertain-ties in both the system‘s structure and external disturbances, and the non-stationarity and dependency of the system signals. Thus, a key difficulty in establishing a mathematical theory of adaptive systems lies in how to deal with complicated nonlinear stochastic dynamical systems which describe the adaptation processes. In this paper, we will illustrate some of the basic concepts, methods and results through some simple examples. The following fundamental questions will be discussed: How much information is needed for estimation? How to deal with uncertainty by adaptation? How to analyze an adaptive system? What are the convergence or tracking performances of adaptation? How to find the proper rate of adaptation in some sense? We will also explore the following more fundamental questions: How much uncertainty can be dealt with by adaptation ? What are the limitations of adaptation ? How does the performance of adaptation depend on the prior information ? We will partially answer these questions by finding some “critical values“ and establishing some “Impossibility Theorems“ for the capability of adaptation, for several basic classes of nonlinear dynamical control systems with either parametric or nonparametric uncertainties.     

Electronic support for knowledge creation in a research institute

This paper focuses on the question how to build an electronic support environment for knowledge creation in a research institute （JAIST）. In order to assess the importance of diverse conditions of scientific creativity, we performed a survey in JAIST, and extracted useful knowledge from the database of survey results. Following the analysis of the theory of academic processes of knowledge creation and the survey findings in JAIST, a computer-based integrated system is proposed. In the aspect of the system design, we postulate that an electronic support environment for academic creativity can be achieved through a seamless integration with Internet, Application Server, Middle Ware, Database and Data Warehouse. The paper addresses issues of knowledge representation in the Electronic Support System for academic research, testing and evaluation issues and conclusions.     

Asymptotic Stability and Balanced Growth Solution of the Singular Dynamic Input-Output System＊

The dynamic input-output system is well known in economic theory and practice. In this paper the asymptotic stability and balanced growth solution of the dynamic input-output system are considered. Under three natural assumptions, we obtain four theorems about asymptotic stability and balanced growth solution of the dynamic input-output system and bring together in a unified manner some contributions scattered in the literature.     

AN AGENT—BASED SIMULATION ON MARKET CONSIDERING KNOWLEDGE TRANSITION AND SOCIAL IMPACT

In this paper, an agent-based simulation about knowledge transition associated with social impact in market is introduced. In the simulation, the genetic algorithm is used to generate the next generation products and a dynamic social impact model is used to simulate how customers are influenced by other customers. The simulation and its results not only show some features and patterns of knowledge transition, but also explore and display some phenomena of business cultures. On the basis of the innovation model of knowledge-based economy, the transition between technical knowledge and products knowledge is discussed, and a fuzzy linear quantification model which can be used to simulate the transition is introduced.     

CALL FOR PAPERS:Special Section on Sensor Array Signal Processing and its Applications in 5G/6G

Sensor arrays provide additional degree of freedom in the spatial domain compared to a single antenna,which,with the aid of advanced signal processing algorithms,can be exploited for interference suppressio n/beamforming,direction of arrival estimatio n,and target tracking and localization.While two prominent technologies in 5G/6G communication system,i.e.,massive MIMO and millimeter(mm)wave communication,generally demand massive antennas,significant advances in antenna arrays are expected to satisfy the requirement of thousands of contemporaneously connected devices.     

SYNCHRONIZATION IN COMPLEX DYNAMICAL NETWORKS

In the past few years, the discovery of small-world and scale-free properties of many natural and artificial complex networks has stimulated increasing interest in further studying the underlying organizing principles of various complex networks. This has led to significant advances in understanding the relationship between the topology and the dynamics of such complex networks. This paper reviews some recent research works on the synchronization phenomenon in various dynamical networks with small-world and scale-free connections.     

A Robust Adaptive Dynamic Programming Principle for Sensorimotor Control with Signal-Dependent Noise

As human beings,people coordinate movements and interact with the environment through sensory information and motor adaptation in the daily lives.Many characteristics of these interactions can be studied using optimization-based models,which assume that the precise knowledge of both the sensorimotor system and its interactive environment is available for the central nervous system(CNS).However,both static and dynamic uncertainties occur inevitably in the daily movements.When these uncertainties are taken into consideration,the previously developed models based on optimization theory may fail to explain how the CNS can still coordinate human movements which are also robust with respect to the uncertainties.In order to address this problem,this paper presents a novel computational mechanism for sensorimotor control from a perspective of robust adaptive dynamic programming(RADP).Sharing some essential features of reinforcement learning,which was originally observed from mammals,the RADP model for sensorimotor control suggests that,instead of identifying the system dynamics of both the motor system and the environment,the CNS computes iteratively a robust optimal control policy using the real-time sensory data.An online learning algorithm is provided in this paper,with rigorous convergence and stability analysis.Then,it is applied to simulate several experiments reported from the past literature.By comparing the proposed numerical results with these experimentally observed data,the authors show that the proposed model can reproduce movement trajectories which are consistent with experimental observations.In addition,the RADP theory provides a unified framework that connects optimality and robustness properties in the sensorimotor system.     

MAN-MACHINE COLLABORATED KNOWLEDGE CREATION IN HWMSE

1 Introduction Science of complexity and complex systems is a relatively new area In wide fields from chemistry, biology, environment, geo-science, climatology to economics and sociology, complexity has been studied from diverse views and understandings Systems science, which could be traced back to Ludwig von Bertalanffy’foundational work on general system theory, plays an active role in complexity studies From system perspectives, relevant concepts often include interaction, feedback, evol…     

AIS—基于文本挖掘的增强型Web信息处理技术

回顾了中文和英文语言环境下的Web文本挖掘现状,阐明了其现阶段的特点和技术瓶颈.之后提出了一种基于Web文本挖掘的网页内容挖掘技术:AIS(Augmented information support),介绍了相关实现所涉及的基础技术和功能.最后将AIS技术应用于香山科学会议网站,开发了AIS4XSSC文本挖掘系统并展示了现阶段其主要功能.实践表明AIS技术能够从大量的Web文本中有效提炼信息,提高用户检索效率并向用户推送有价值的信息.     

研讨厅系统实现方法及技术的研究

在研讨厅研究及系统实现的基础上 ,论述了研讨厅的作用、特点及解决的问题 ,并提出了研讨厅系统实现的关键问题 ,包括如何实现从定性到定量 ,适于研讨厅的研讨过程、研讨模板、面向问题重构的概念和内涵 .利用新的计算机技术 ,构建了一种研讨厅的系统结构及其综合集成系统 .     

面向复杂决策任务的综合集成决策研讨总体框架设计

从群体决策任务结构化理论出发,分析了复杂决策任务研讨过程的层次结构和组合机理,结合从定性到定量的综合集成方法,研究提出了一种适合软件实施需求,能够充分实现人机结合的研讨信息分解集成框架,在此基础上设计实现了一种可付诸于实施的研讨厅系统———开放式群体决策研讨平台GASS,并给出一个企业开拓新市场的决策实例.     

Smart Cities and M<Superscript>3</Superscript>: Rapid Research,Meaningful Metrics and Co-Design

The research described in this paper is undertaken under the banner of the smart city, a concept that captures the way urban spaces are re-made by the incursion of new technology. Much of smart is centred on converting everyday activities into data, and using this data to generate knowledge mediated by technology. Ordinary citizens, those that may have their lives impacted by the technology, usually are not properly involved in the ‘smartification’ process. Their perceptions, concerns and expectations should inform the conception and development of smart technologies at the same extent. How to engage general public with smart cities research is the central challenge for the Making Metrics Meaningful (MMM) project. Applying a rapid participatory method, ‘Imagine’ over a five-month period (March – July) the research sought to gain insights from the general public into novel forms of information system innovation. This brief paper describes the nature of the accelerated research undertaken and explores some of the themes which emerged in the analysis. Generic themes, beyond the remit of an explicit transport focus, are developed and pointers towards further research directions are discussed. Participatory methods, including engaging with self-selected transport users actively through both picture creation and programmatically specific musical ‘signatures’ as well as group discussion, were found to be effective in eliciting users’ own concerns, needs and ideas for novel information systems.     

空间军事系统综合集成研讨厅内容体系的研究与建设

在详细研究了高层研讨厅、低层研讨厅和作战模拟与训练演习系统三个组成部分的基础上 ,给出了空间军事系统综合集成研讨厅内容体系 ,根据实际军事斗争需要 ,实现研讨厅建设的总目标 .文中还分析了每个组成部分应当以军事任务为牵引 ,以组成结构为基础 ,进行功能需求分析 ,建设一个具有功能相对完善、结构相对完整 ,各部分关系相互协调的研讨厅体系 .     

空间军事系统综合集成研讨厅体系功能需求分析

本文在空间军事系统综合集成研讨厅内容体系研究的基础上，以其三个组成部分（高层研讨厅、低层研讨厅和作战模拟与训练演习系统）为研究对象，结合实际需要，实现研讨厅建设的总目标。为此，本文详细分析了每个组成部分应当完成的任务和相互间的组织协调关系。总之，研讨厅建设应以总目标为牵引，以组成结构为基础，进行功能需求分析，力求达到有的放矢，不失研讨厅建设的总目标，实现具有功能相对完整、结构相对完整，各部分关系协调一致的研讨厅体系。     

综合集成的内容与方法——复杂巨系统问题研究

本文归纳了解决复杂巨系统问题时遇到的困难,给出了解决复杂巨系统问题的一般分析步骤,研究了用综合集成技术研究解决复杂巨系统问题的方法。综合集成包括“知识集成”和“系统综合”两层含义。“知识集成”包括四项支撑技术：分布式网络、信息融合、定性定量相结合、专家研讨。     

综合集成与知识科学

对以钱学森教授为主首创的处理开放复杂巨系统问题的方法——综合集成以及知识科学近年来的发展作一个简要的综述 .首先介绍了日益引起重视的知识科学 ,给出我们对知识科学的整体认识 ;接着介绍了国内外一些综合与集成方法 ,并介绍了作者根据近年来的研究而提出的综合集成知识系统 ,最后以可持续发展和宏观经济决策 2个案例来说明两者的结合 .     

Further Investigation of Characteristic Relation in Incomplete Information System

In the recent years, the method to expand Pawlak's rough set model in different kinds of information systems has become a hot topic. This article presents explorative research focusing on the transition from the traditional information system to a complex system—the incomplete information system. In such information system, “do not care” and lost unknown attribute values coexist. With a further investigation of Grzymala-Busse's characteristic relation in the incomplete information system, two unreasonable situations in the analysis of the classified problem are presented. To conduct sound classification in the incomplete information system, a new characteristic relation is proposed and by use of this new characteristic relation, the complete covering on the universe is formed. Based on the maximal complete compatible classes in the complete covering, two notions of the knowledge representation system are presented and some important properties associated with these knowledge representation systems are discussed. For further illustration, an example is analyzed. The research is meaningful both in theory and in applications for the extension of the rough set theory in incomplete information systems.