基于多自治体的服装集成制造系统

提出了一种基于多自治体智能节点的,构成信息化服装集成制造系统的新方法,这种方法采用Servlet技术,采用请求——响应的Web服务模式来进行网络数据库的访问,将服装制造过程各单元,诸如服装CAD系统、计算机控制的自动裁床、智能吊挂生产系统等自动孤岛集成起来,构成一个分布式多自治体的服装制造系统．本文还具体阐述了制造系统中多自治体的基本结构和多自治体之间的组织方式．这种技术的应用可以实现了服装设计、裁剪、缝制及其余管理各个子系统达到真正的无缝集成．     

可拓学与知识管理交叉研究视角下的问题智能化处理

目的 虽然人工智能在机器学习和确定性问题求解方面取得了重要进展,但是在管理实践中更普遍的矛盾问题处理方面仍旧主要依赖于个体的经验,其智能化求解是学科交叉广、科学价值高的学术难题,因此亟需开拓问题智能化处理的新方向.方法 在综述国内外问题处理相关研究现状的基础上,回顾可拓学在矛盾问题处理方面的研究进展,分析可拓学在矛盾问题智能化处理方面的主要流程和方法,结合人工智能技术,从可拓学与知识管理交叉研究的视角,指出了问题智能化处理的几种新方向.结论 通过可拓学与智能知识管理的交叉研究,可以进一步利用新一代信息技术,按照一定的程序,系统化生成处理问题的所有可能的策略,从而提高问题求解从不确定性和随机性向必然性转化的程度,探索构建中国特色、中国风格的问题智能处理理论与方法.     

Agent的PASS—BDI模型

Agent的BDI模型主要基于Bratman提出的理性主体理论，未能充分体现Agent主动性的认知过程，使Agent的问题求解和心智状态之间的关系未得到充分表达，且难于编程实现。将Das等人提出的计划—注意—同时性加工—继时性加工认知过程模型引入Agent的理论研究中，建立了Agent的PASS—BDI模型，利用多价π—演算从心智状态，认知过程，整体行为等几个方面刻画了该模型的静态和动态特征，并将研究结果应用于多Agent组织中Agent行为特征的刻画。PASS—BDI模型加强了对Agent主动性认知过程的刻画，且易于编程实现。     

Can artificially intelligent agents really be conscious?

Mind and intelligence are closely related with the consciousness. Indeed, artificial intelligence (AI) is the most promising avenue towards artificial consciousness (AC). However, in literature, consciousness has been considered as the least amenable to being understood or replicated by AI. Further, computational theories of mind (CTMs) render the mind as a computational system and it is treated as a substantial hypothesis within the purview of AI. However, the consciousness, which is a phenomenon of mind, is partially tackled by this theory and it seems that the CTM is not corroborated considerably in this pursuit. Many valuable contributions have been incorporated by the researchers working strenuously in this domain. However, there is still scarcity of globally accepted computational models of consciousness that can be used to design conscious intelligent machines. The contributions of the researchers entail consciousness as a vague, incomplete and human-centred entity. In this paper, attempt has been made to analyse different theoretical and intricate issues pertaining to mind, intelligence and AC. Moreover, this paper discusses different computational models of the consciousness and critically analyses the possibility of generating the machine consciousness as well as identifying the characteristics of conscious machine. Further, different inquisitive questions, e.g., “Is it possible to devise, project and build a conscious machine?”, “Will artificially conscious machines be able to surpass the functioning of artificially intelligent machines?” and “Does consciousness reflect a peculiar way of information processing?” are analysed.     

Integration of human behavioural aspects in a dynamic model for a manufacturing system

The computational simulation of human intelligent behaviour has been one of the main research topics in the artificial intelligence (AI) domain. Therefore, a great number of behavioural models were proposed considering emotional, cognitive and psychological factors to simulate the human behaviour in different domains such as military or manufacturing systems. In addition to psychological factors, the social state of a group of workers plays a critical role in rational decision-making, perception, human interaction, and human intelligence. Thus, it is judicious to analyse the workers’ behaviour at work and to integrate their needs and requirements in manufacturing systems models in order to improve the simulation accuracy. In this context, this paper suggests a graphical and a mathematical representation model of workers’ behaviours as well as the ties that can exist among them. The model is also extended to consider inter-worker social relations that can influence the individual performance.     

A hybrid case-based reasoning CAD system for injection mould design

Injection mould design generally lies on the critical path of a new product development. The design efficiency will have significant impact on the overall lead time of a new product. This paper presents a prototype injection mould-design system using a hybrid case-based reasoning (HCBR) approach. Case-based reasoning (CBR) is a solving paradigm that uses previous episodes on solving problems similar to the problem at hand (the new problem) as the basis for solving the new problem. In this hybrid system, CBR is incorporated with generalized design knowledge, and provides a flexible and comprehensive model of design. The knowledge base of the system would be accessed by mould designers through interactive programs so that their own intelligence and experience could also be incorporated with the total mould design. The approach provides a workable model of mould design system with CBR and knowledge-based expert system intelligent support, which could suggest good and proven design solutions to new design problems quickly, avoiding the time necessary to create those designs from scratch, for the plastic products manufacturing industry.     

面向印制电路板钻孔任务动态调度的短视策略

印制电路板钻孔任务因随机到达和工艺要求而难以调度。考虑该问题的NP难性质,提出基于优先规则和智能算法的短视策略。该策略采用事件驱动的再调度机制,在任务到达和任务完工时触发优化算法对当前未开工任务进行决策。为了高效求解每个决策时刻的优化问题,构建了嵌入局部优势定理的模拟退火和变邻域搜索算法,其初始解由优先规则获得。通过计算实验,在不同调度环境下对比两种智能算法与经典优先规则的表现。实验结果表明,智能算法在多数目标下的优化效果较优先规则可提升20%以上,变邻域搜索的优化效果略好于模拟退火,但是模拟退火的计算效率高一倍。     

基于智能多代理的复杂场景钢坯字符切分算法

在生产线钢坯检测识别过程中,如何准确地切分生产线实际复杂场景下的钢坯端面字符是一个高度复杂的智能问题.为了解决这一复杂问题,本文提出了一种基于智能多代理者的字符切分处理方法,将分控制层中的字符区域分割与切分、区域合并、区域分裂、特征计算等功能子程序作为个体代理者,主控制层作为主控代理者对这些个体代理者根据具体需要进行统一分工协调,同时各子代理者的切分信息反馈给主控代理者作为分析、控制各子代理者的重要因素,进而完成钢坯号字符的精确切分.实验结果表明,本文提出的算法能对复杂场景中的钢坯字符完成精确的切分,具有良好的稳定性与准确性,解决了复杂场景中的钢坯字符准确切分的问题,为后续钢坯字符的识别提供了保证.     

人工智能的计量校准

针对人工智能的计量校准,阐述了其紧迫性、必要性以及可行性.提出了2种不同的人工智能计量解决方案.其一为基础方式,从智能的7个维度出发,分别进行语言智能、数理逻辑智能、空间智能、肢体运动智能、音乐智能、人际关系智能、内省智能的计量校准研究,然后,针对同时含有两种以上智能的多元智能系统,进行面向具体任务目标的综合加权,给出...     

智能时代用户体验特点及其测量方法

目的 对智能系统与产品的时代特点及其用户体验测量方法进行分析,为用户体验测量方法提供新的技术研究思路。方法 以用户为中心的设计理论为基础,通过描述智能时代的系统与产品创新设计的用户体验特点、标准及需求,介绍了融合新技术特征的智能系统或产品在各领域的用户体验研究,突出创新设计驱动的以人为本思想,同时分析了产品全生命周期人机交互过程需求,介绍了一种新的基于多通道数据同步技术的定量化、客观的用户体验测量方法的功能及应用。结论 智能时代的产品与系统在体现智能技术主导的同时,也强调产品全生命周期的用户体验与融合先进技术的测量方法结合,促进了用户体验研究测量方法的革新,提升了系统或产品的社会需求价值,对实现用户体验战略化具有重要的意义。     

Agent-based project scheduling

Agent technology offers a new way of thinking about many of the classic problems in operations research. Among these are problems such as project scheduling subject to resource constraints. In this paper, we develop and experimentally evaluate eight agent-based algorithms for solving the multimode, resource-constrained project scheduling problem. Our algorithms differ in the priority rules used to control agent access to resources. We apply our approach to a 51-activity project originally published by Maroto and Tormos [1]. We solve the problem using two types of agent-based systems: (i) a system of simple, reactive agents that we call basic agents; and (ii) a system of more complex, deliberative agents that we call enhanced agents. Of the eight priority rules tested, we find that priority based on shortest processing time performs best in terms of schedule quality when applied by basic agents while the priority based on earliest due date performs best when applied by enhanced agents. In comparing agents across priority rules, we find that enhanced agents generate much better schedules (with makespans up to 66% shorter in some cases) and require only slightly more computation time.     

Does cumulative advantage affect collective learning in science? An agent-based simulation

Agent-based simulation can model simple micro-level mechanisms capable of generating macro-level patterns, such as frequency distributions and network structures found in bibliometric data. Agent-based simulations of organisational learning have provided analogies for collective problem solving by boundedly rational agents employing heuristics. This paper brings these two areas together in one model of knowledge seeking through scientific publication. It describes a computer simulation in which academic papers are generated with authors, references, contents, and an extrinsic value, and must pass through peer review to become published. We demonstrate that the model can fit bibliometric data for a token journal, Research Policy. Different practices for generating authors and references produce different distributions of papers per author and citations per paper, including the scale-free distributions typical of cumulative advantage processes. We also demonstrate the model’s ability to simulate collective learning or problem solving, for which we use Kauffman’s NK fitness landscape. The model provides evidence that those practices leading to cumulative advantage in citations, that is, papers with many citations becoming even more cited, do not improve scientists’ ability to find good solutions to scientific problems, compared to those practices that ignore past citations. By contrast, what does make a difference is referring only to publications that have successfully passed peer review. Citation practice is one of many issues that a simulation model of science can address when the data-rich literature on scientometrics is connected to the analogy-rich literature on organisations and heuristic search.     

Agent-based project scheduling: computational study of large problems

We present in this paper the results of a computational study for project scheduling based on new ideas for project representation taken from digital circuit technology (Knotts et al. , 1998a) and a solution approach based on the artificial intelligence notion of agent technology. We experimented with projects with up to 10 000 stochastic duration activities which can be executed in a number of modes requiring renewable, nonrenewable, and periodically renewable resources. This study is about agent implementation in a project scheduling domain. It compares agent types and priority rules with respect to their impact on project schedule duration and computational performance. This work demonstrates: (i) that artificial intelligence concepts of agent technology can be successfully implemented for project scheduling; and (ii) in conducting project scheduling studies we can experiment successfully with large project networks. Both points made in this research are new.     

基于神经网络的智能诊断

人工智能与诊断理论的结合形成了智能诊断,早期发展的模拟人脑思维推理的、基于知识的专家系统以串行运行的格式进入设备诊断领域,形成了基于知识的诊断推理专家系统,国内外已有许多成熟的商品化软件系统。近几年新发展起来的人工智能的一个分支－－人工神经网络模仿人脑物理结构以其强大的并行运算和联想能力非常适合于设备诊断中状态识别,本单位研制的通用型神经网络智能诊断系统,已达到商品化水平,并已在生产线上运行。     

Patents intelligence from legal and commercial perspectives

Competitive intelligence using patents has two major focuses, commercial intelligence and legal intelligence. Where companies use the same technology to solve the same problem, both commercial and legal issues need to be explored with patent intelligence. Where the same technology is used to solve a different problem, issues lean toward the legal end of the spectrum. Where a different technology is used to solve the same problem, the main concerns are commercial. Commercial patent intelligence is best conducted by focusing on patents that a company publishes outside the home country. Legal patent intelligence requires that all patents in a considered technology be examined. Exceptions analysis is particularly useful in commercial patent intelligence and centres around learning a company's standard patenting practices so that patents treated differently can be isolated and examined for possible importance.     

The role of soft computing in intelligent machines

An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.     

轻武器弹药智能化包装研究

目的 着眼未来战场信息化和智能化的特点,立足创新弹药智能化包装方法,提高弹药快速保障能力。方法 从轻武器弹药包装的内包装、中间包装、外包装、集合包装等智能化包装要素入手,对其作战需求、原理、样机制作、保障系统及结构进行了认真思考和充分论证。结果 研究明确了标准化包装、集装化运输、成套化供应、智能化管理的设计方案,探索制作了系统样机。结论 通过试用,验证了弹药智能化包装系统的功能符合日常管理需要,能够满足适时、适地、适量、适用的精确化保障目标要求。     

钱学森与管理科学

钱学森教授在从科技专家到思想家的发展历程中,一贯强调组织管理的重要作用。文章从钱学森教授提出发展管理科学关键在提高认识,强调系统工程在组织管理方面的作用,提倡从整体上考虑并解决问题,推动自然科学与社会科学的结合,以及坚持按照国情发展管理科学等五个方面,论述了钱学森教授在发展我国管理科学方面的指导性贡献。［关键词］钱学森;管理科学;管理     

Social aspect of sustainable packaging

Sustainability is one of the ‘buzz’ words that is highly discussed in the area of packaging nowadays. For many product manufacturing business, incorporation of sustainability principles into their business practice can only be visualized by others in the end product through packaging. Besides the criteria, underlying concepts and principles, most discussions towards achieving goals for sustainable packaging are focused on details of models and practices adopted by the industry, and the effectiveness and practicality of these practices in balancing the economic profits and environmental benefits. While the economic and environmental bases of packaging sustainability have been examined and discussed in great detail, the same is not true of social consideration. Although the success of sustainable packaging development actually relies on both technological development and social considerations, many of the social aspects of sustainable packaging are often overlooked. Although many companies have been putting the efforts and initiatives to elevate sustainability from an abstract goal into an immediate priority, relatively little is known about the consumers' insights of packaging sustainability. Recognizing the consumers as the final arbiter of the success of sustainable packaging, this paper will explore consumers' perceptions on the sustainable packaging concept, their perceptions of the impact to the environment and discuss factors that drive consumers' preferences and purchase decision. Discussion and information gathered in this paper is aimed to stimulate understanding on the importance of the social dimension of packaging sustainability and its role in supporting the efforts to improve sustainability practice. Copyright © 2010 John Wiley & Sons, Ltd.     

大数据时代人工智能赋能社会设计前景研究

目的 聚焦当前信息时代下的大数据环境和日益突出的社会问题,探究人工智能的发展会为社会设计的思维与方法、演进与智能化带来怎样的影响。方法 首先厘清社会设计的概念及其内在的逻辑与模式,然后比较分析人工智能赋能设计产业所展现出的新特点,通过实践案例探究其对社会设计发展可能产生的影响。结果 在万物数据化、智能化的今天,人工智能的发展逐步渗入到设计产业中,不仅丰富了设计创作的工具和流程,更是对传统的设计方法、设计思维和评价标准进行了全方位的语义升维。结论 基于量化数据的计算设计呈现出系统化、个性化及实时性等特征,由算法与大数据所衍生出的新思维模式将以往不确定的问题转化为直观的数据问题,能够与社会设计形成良好的互补关系。