Towards intelligent autonomous control systems: Architecture and fundamental issues

Autonomous control systems are designed to perform well under significant uncertainties in the system and environment for extended periods of time, and they must be able to compensate for system failures without external intervention. Intelligent autonomous control systems use techniques from the field of artificial intelligence to achieve this autonomy. Such control systems evolve from conventional control systems by adding intelligent components, and their development requires interdisciplinary research. A hierarchical functional intelligent autonomous control architecture is introduced here and its functions are described in detail. The fundamental issues in autonomous control system modelling and analysis are discussed.     

A fault tolerant single-chip intelligent agent with feature extraction capability

Autonomy and adaptability are key features of intelligent agents. Many applications of intelligent agents, such as the control of ambient intelligence environments and autonomous intelligent robotic systems, require the processing of information coming in from many available sensors to produce adequate output responses in changing scenarios. Autonomy, in these cases, applies not only to the ability of the agent to produce correct outputs without human guidance, but also to its ubiquity and/or portability, low-power consumption and integrability. In this sense, an embedded electronic system implementation paradigm can be applied to the design of autonomous intelligent agents in order to satisfy the above mentioned characteristics. However, processing complex computational intelligence algorithms with tight delay constraints in resource-constrained and low power embedded systems is a challenging engineering problem. In this paper a single-chip intelligent agent based on a computationally efficient neuro-fuzzy information processing core is described. The system has been endowed with an information preprocessing module based on Principal Component Analysis (PCA) that permits a substantial reduction of the input space dimensionality with little loss of modeling capability. Moreover, the PCA module has been tested as a means to achieve deep adaptability in changing environment dynamics and to endow the agent with fault tolerance in the presence of sensor failures. For data driven trials and research, a data set obtained from an experimental intelligent inhabited environment has been used as a benchmark system.     

群智体系网络结构的自治调节:从生物调控网络结构谈起

群体智能作为人工智能2.0时代最突出的研究方向之一,受到了工业界和学术界研究者们的广泛关注。传统的人工智能模型倾向于使用全连通网络结构,认为全连通网络结构的人工智能模型具有更高的准确率。然而,在面对存在强干扰的复杂对抗环境时,智能决策体系需要面对由通信干扰甚至针对性攻击所造成的系统结构扰动。在不失准确性的前提下,为了能够更快、更稳定地进行实时响应,需要智能系统的结构具有实时自治响应调整机制。此类自治响应调整机制在自然界中的调控网络中很常见。文中通过引入DReSS表征族来定量分析随机网络与真实网络中结构扰动对于系统演化的影响,对比了不同网络结构对于结构扰动的抗干扰能力,并提出了一套群智体系网络结构的自治调节构想。     

Towards Intelligent Organisational Information Systems

It has been argued in the literature that although specific types of computer-based information systems (CBIS) are powerful tools in certain parts of the decision-making processes in modern organisations, none of them provides integrated support. This lack becomes even more acute when one considers the operation of CBIS within an organisational setting where consistent assistance of a multitude of users in different departments is required, together with facilities for modelling such features as cooperation, conflict, negotiation, etc. On the other hand, there are indications that the incorporation of abilities such as perception, interpretation, reasoning, explanation, goal-setting, and learning in computer-aided support would greatly enhance the aforementioned decision-making processes. This paper reviews the evolution of CBIS, and attempts to synthesise current research towards the goal of competent and intelligent aiding of decision-making in organisational settings. The main argument of the paper is that decision-making functions in multi-participant organisations can be facilitated by the use of intelligent software entities with autonomous processing capabilities which possess coordination and negotiation facilities and are organised in distributed, hierarchical societies. This paper presents a conceptual definition of these entities, outlines their structural characteristics, and describes a framework for research towards their development.     

Integration and control of intelligence in distributed manufacturing

The area of intelligent systems has generated a considerable amount of interest—occasionally verging on controversy—within both the research community and the industrial sector. This paper aims to present a unified framework for integrating the methods and techniques related to intelligent systems in the context of design and control of modern manufacturing systems. Particular emphasis is placed on the methodologies relevant to distributed processing over the Internet. Following presentation of a spectrum of intelligent techniques, a framework for integrated analysis of these techniques at different levels in the context of intelligent manufacturing systems is discussed. Integration of methods of artificial intelligence is investigated primarily along two dimensions: the manufacturing product life-cycle dimension, and the organizational complexity dimension. It is shown that at different stages of the product life-cycle, different intelligent and knowledge-oriented techniques are used, mainly because of the varied levels of complexity associated with those stages. Distribution of the system architecture or system control is the most important factor in terms of demanding the use of the most up-to-date distributed intelligence technologies. A tool set for web-enabled design of distributed intelligent systems is presented. Finally, the issue of intelligence control is addressed. It is argued that the dominant criterion according to which the level of intelligence is selected in technological tasks is the required precision of the resulting operation, related to the degree of generalization required by the particular task. The control of knowledge in higher-level tasks has to be executed with a strong involvement of the human component in the feedback loop. In order to facilitate the human intervention, there is a need for readily available, user-transparent computing and telecommunications infrastructure. In its final part, the paper discusses currently emerging ubiquitous systems, which combine this type of infrastructure with new intelligent control systems based on a multi-sensory perception of the state of the controlled process and its environment to give us tools to manage information in a way that would be most natural and easy for the human operator.     

基于平行测试的认知自动驾驶智能架构研究

在大数据、云计算和机器学习等新一代人工智能技术的推动下, 自动驾驶的感知智能在近年来得到显著的提升与发展. 然而, 与人类驾驶过程中隐含的以自我目的实现为引导的自探索性和自主性相比, 现阶段自动驾驶技术主要以辅助驾驶功能为主, 还停留在以被动感知、规划与控制为主的初级智能自动驾驶阶段. 为实现车辆智能从数据驱动的环境感知、辅助决策、被动规划到知识驱动的场景认知、推理决策、主动规划的提升, 亟需增强车辆自身对复杂外界信息归纳提炼、推理决策、评价估计等类人能力. 首先回顾自动驾驶关键技术演化及其应用发展历程; 随后分析测试对车辆智能评估的效用; 然后基于平行测试理论, 提出自动驾驶车辆认知智能训练、测试与评估空间的构建方法, 并设计基于平行测试的认知自动驾驶智能训练框架. 该项研究工作预期能为推动自动驾驶从感知智能向认知智能的升级提供可行的技术支撑与实现路径.     

智能系统全生命周期安全测试理论与方法

人工智能技术在公共、国防安全领域得到了广泛应用,然而智能系统的安全性面临极大挑战。如何有效、全面、深入地对智能系统进行安全测试成为解决当前智能系统安全问题的重要途径。近年来,国内外高度重视智能系统的安全性问题,开展了大量的安全测试理论方法研究并出台了大量相关政策文件。针对智能系统面临的安全问题,本文详细阐述了面向智能系统全生命周期的安全测试理论与方法。首先,本文说明了智能系统的特点、安全内涵及安全机理;接着,本文结合模型训练、模型推理、模型部署三个主要生命周期阶段,详细地阐述了智能系统面临的安全性挑战和测试理论方法;最后,本文从标准、平台等角度阐明了构建智能系统安全测试支撑体系的方式,分析了自动驾驶典型场景下的智能系统安全测试案例,并给出了未来展望。开展智能系统安全测试理论和方法体系的建设,可有效规避系统潜在风险和质量缺陷,是实现人工智能算法可解释、可信赖的基本路径,对于确保人工智能技术安全、可靠、可控具有重要意义。     

基于生态演化的通用智能系统结构模型研究

从系统论、认知神经科学和生态演化的角度看, 智能是指生物体根据环境、条件、目标, 自适应地调整自身或调度各种资源实现目标的能力, 智能起源于生命, 智能是生物的基本特征.借助于脑神经系统演化的历史, 展示了自然智能的演化过程, 并由此构建了一个基于生态演化的通用智能系统结构模型, 系统地分析了一般智能系统的普遍性、开放性、动态演化性、相对稳定性、功能性、结构性、依附性、相对独立性、可延续性等基本特征.论文根据智能演化进程将智能系统分为7级, 利用智能系统结构模型分类探索专用人工智能和通用人工智能的发展方向以及有关智能系统的学习方法.这些工作对人工智能和智能科学基础理论研究与应用具有一定的启发意义.     

Emergence of intelligence in next-generation manufacturing systems

In the paper we propose a fundamental shift from the present manufacturing concepts and problem solving approaches towards new manufacturing paradigms involving phenomena such as emergence, intelligence, non-determinism, complexity, self-organization, bottom-up organization, and coexistence with the ecosystem. In the first part of the paper we study the characteristics of the past and the present manufacturing concepts and the problems they caused. According to the analogy with the terms in cognitive psychology four types of problems occurring in complex manufacturing systems are identified. Then, appropriateness of various intelligent systems for solving of these four types of problems is analyzed. In the second part of the paper, we study two completely different problems. These two problems are (1) identification of system in metal forming industry and (2) autonomous robot system in manufacturing environment. A genetic-based approach that imitates integration of living cells into tissues, organs, and organisms is used. The paper clearly shows how the state of the stable global order (i.e., the intelligence) of the overall system gradually emerges as a result of low-level interactions between entities of which the system consists and the environment.     

The road to intelligence

It is argued that robotic platforms are the way forward towards building intelligent systems, where multiple sensors and manipulation are used for cognitive processes. It is also argued that the cue for developing the right architecture for such a system is human language.     

智能安全内涵与体系构建探讨

随着人工智能在各行业的推广应用,人工智能给生活、生产带来便利的同时,其破坏作用和隐患也引起了各国政府、机构的重视。因此,人工智能技术及其应用所引起的安全问题受到更多关注。但是,从智能的形态角度看,智能安全与人工智能安全在内涵上还有很多区别。本文首先阐明智能安全的内涵,指出人工智能安全实际上主要是技术层面的智能安全,但智能安全不仅涉及技术安全,还包括智能系统在各行业广泛普及带来的国家层面的安全问题,以及机器智能、混合智能等新智能形态发展给人类整体带来的潜在风险。在此基础上,本文构建了智能安全体系并给出了具体措施。狭义的人工智能安全与广义的智能安全理念相结合,有利于确保整个国家在人类文明发展过程中把握先机。     

智能系统的广义智能定性评价之研究

本文专门研究智能系统的智能特性和智能水平评价,旨在促进其健康发展。采用的主要方法是：在图灵测试的基础上,借鉴了人的智商测试方法,运用了广义人工智能的广义思想,提出了广义智能评价理论体系。该理论体系包括了一个关于广义智能评价的定义、特指系统的性能和特指系统技术的两个广义智能标准、评价产品或系统智能时使用的三个广义规范,提出了广义智商算法、广义智能评价的定性和定量评价方法及评价规则,它留下的广义空间可包容不同类型的智能系统作为其评价对象。在实施评价的过程中,采用共享法、仿真法和人机结合等测试方法,举例说明了对典型智能控制系统的智能水平评价和对智能移动机器人自识别特定对象的智能特性评价结果。     

集成ERP 的移动商业智能系统

集成ERP的商业智能虽然可以满足企业对海量数据进行智能分析与挖掘以辅助决策的需求,但依然难以随时随地提供实时数据以快速响应市场变化和进行有效决策.在现有商业智能研究基础上,提出了集成ERP的实时移动商业智能概念,运用中间件数据集成技术和面向服务架构,设计了一个扩展性强、低耦合和跨平台的移动商业智能系统体系架构,利用Android在智能移动终端上开发了一个与服务器端ERP系统相集成的商业智能系统,并通过实例对该系统在移动终端上的实现技术进行了详细的描述.     

大规模类脑计算系统BiCoSS: 架构、实现及应用

人脑具有协同多种认知功能的能力与极强的自主学习能力, 随着脑与神经科学的快速发展, 亟需计算结构模拟人脑的、性能更强大的计算平台进行人脑智能与认知行为机制的进一步探索. 受人脑神经机制的启发, 本文提出了基于神经认知计算架构的众核类脑计算系统BiCoSS, 该系统以并行计算的现场可编程门阵列(Field-programmable gate array, FPGA)为核心处理器, 以地址事件表达的神经放电作为信息传递载体, 以具有认知计算功能的神经元作为信息处理单元, 实现了四百万神经元数量级大规模神经元网络认知行为的实时计算, 填补了从细胞动力学层面理解人脑认知功能的鸿沟. 实验结果从计算能力、计算效率、功耗、通信效率、可扩展性等方面显示了BiCoSS系统的优越性能. BiCoSS通过人脑信息处理的计算架构以更贴近神经科学本质的模式实现了类脑智能; 同时, BiCoSS为神经认知和类脑计算的研究和应用提供了新的有效手段.     

Computation and the Three Worlds

Discussions about the achievements and limitations of the various approaches to the development of intelligent systems can have an essential impact on empirically based research, and with that also on the future development of computer technologies. However, such discussions are often based on vague concepts and assumptions. In this context, we claim that the proposed `three-world ontology' offers the most appropriate conceptual framework in which the basic problems concerned with cognition and computation can be suitably expressed and discussed, although the solutions of some of these problems seem to lie beyond the horizon of our current understanding. We stress the necessity to differentiate between authentic and functional cognitive abilities; although computation is not a plausible way towards authentic intelligence, we claim that computational systems do offer virtually unlimited possibilities to replicate and surpass human cognitive abilities on the functional level.     

新一代知识图谱关键技术综述

近年来,国内外在新一代知识图谱的关键技术和理论方面取得了一定进展,以知识图谱为载体的典型应用也逐渐走进各个行业领域,包括智能问答、推荐系统、个人助手等.然而,在大数据环境和新基建背景下,数据对象和交互方式的日益丰富和变化,对新一代知识图谱在基础理论、体系架构、关键技术等方面提出新的需求,带来新的挑战.将综述国内外新一代知识图谱的关键技术研究发展现状,重点从非结构化多模态数据组织与理解、大规模动态图谱表示学习与预训练模型、神经符号结合的知识更新与推理3方面对国内外研究的最新进展进行归纳、比较和分析.最后,就未来的技术挑战和研究方向进行展望.     

运行于区块链上的智能分布式电力能源系统:需求、概念、方法以及展望

智能分布式电力能源系统（Intelligent distributed,electrical energy systems,IDEES）具有组件种类繁多,数量庞大,管理困难,利润低微等特点,导致传统中心化的运营管理不再适合此类系统,而区块链技术可能是推行大规模分布式智能电力能源系统重要的技术路径.由于电力能源系统是一种具有社会和技术双重属性的系统,从而注定了其在用区块链实现运行时,必然需要多种区块链来描述和建模其不同的属性,在文中称之为“区块链群”.具体来说,从底层到高层,这个区块链群由分布式数据存储与服务区块链、智能资产管理区块链、电力系统分析区块链、智能合约运营区块链和智能电力交易支付区块链组成.基于区块链技术、分布式文件服务技术、分布式电力系统分析与管理技术,这些不同层次和功能的区块链自我组织、互相协助,最后形成一个分布式自主的电力能源运行系统.在此复杂系统中,频繁而深度的计算与交互衍生出系统智能,笔者期望这种智能将促成稳定、可靠、有效的电力能源生产、传输与消费.     

智能海洋机器人技术进展

智能海洋机器人是可以在复杂海洋环境中执行各种任务的智能化无人平台, 包括智能水下机器人和智能水面机器人. 基于实践和在相关技术难题上的经验, 提出了一些关键技术问题的解决方案. 在智能水下机器人方面, 探讨了体系结构、运动控制、智能规划与决策和系统仿真等关键技术. 在智能水面机器人方面, 探讨了快速性和智能化问题. 我国在智能海洋机器人技术研究方面已经取得了较大的进步, 但距离全面应用还有很大差距.     

Next Generation University Library Information Systems Based on Cooperative Learning

An integrated library information system is a resource planning system for a library, used to track resources owned, bills paid, orders made, and patrons who have borrowed. In our research, we focused on university library information systems (ULISs). We identified an important research question regarding their main limitation in offering intelligent help to the students in their documentation/learning. We identified the importance of the endowment of ULISs with artificial intelligence. In this article, we analyzed different aspects related to the presence of computational intelligence in ULISs and intelligence of ULISs. Finally, we proposed a complex next generation ULIS based on a hybrid cooperative learning, being able to offer an intelligent help for personalized learning of students. We defined some novel paradigms in the context of a novel kind of cooperative hybrid personalized learning, such as learning role and sub-role; and learning intelligence level.     

自动化科学与技术发展方向

本文结合中国自动化科学与技术的发展状况和中国绝大多数大学设有自动化专业的现状,借鉴自动化科学与技术发展历程中的成功经验,结合国家社会经济发展和国家安全对自动化系统的未来需求,以生产制造系统、重要运载工具和人参与的信息物理系统为主要对象,以自动化系统的发展方向—智能自主控制系统、智能优化决策系统和智能优化决策与控制一体化系统的愿景功能为目标,以研究实现愿景功能的建模、控制与优化新算法和新的自动化系统的设计方法和实现技术以及结合重大应用领域开展的应用研究为主线,提出了自动化科学与技术的发展方向,并结合新兴应用领域对自动化科学与技术的需求与挑战,提出了未来自动化科学与技术的发展方向.