本文旨在讨论智联网(Internet of minds,Io M)的基本概念,核心问题和关键平台技术.首先阐述智联网概念的智能时代发展需求和科学哲学思想基础,然后阐述智联网技术的背景、定义、实质,及其实现协同认知智能的目标,并举例说明其前沿应用领...本文旨在讨论智联网(Internet of minds,Io M)的基本概念,核心问题和关键平台技术.首先阐述智联网概念的智能时代发展需求和科学哲学思想基础,然后阐述智联网技术的背景、定义、实质,及其实现协同认知智能的目标,并举例说明其前沿应用领域,包括物理信息社会系统、软件定义系统及流程、工业智联网.接下来探讨智联网的核心问题:知识的获取、知识的协同表征和传递、以及知识的关联和协同运行.最后简单描述了智联网的关键平台技术,包括虚实平行的平台体系和基于互联网、物联网、区块链和软件定义网络的社会化通信计算平台,为分布式、自组织、自运行的安全智联网系统提供基础设施.展开更多
动态网民群体(cyber-enabled social movement organizations,CeSMOs)将是近期信息、控制、智能科学等领域的研究焦点.本文简述CeSMOs的背景、现状、趋势和意义,并提出利用基于ACP概念的计算与平行系统方法来研究动态网民群体.通过人工...动态网民群体(cyber-enabled social movement organizations,CeSMOs)将是近期信息、控制、智能科学等领域的研究焦点.本文简述CeSMOs的背景、现状、趋势和意义,并提出利用基于ACP概念的计算与平行系统方法来研究动态网民群体.通过人工组织对CeSMOs进行建模表示,采用计算实验对其进行分析评估,利用平行执行对其监控和管理.在此基础上,进一步探讨社会计算与平行系统的未来研究方向及方法.最后简要评述相关研究工作在产业发展中的可能作用及对社会演化的可能影响.展开更多
The development of machine learning in complex system is hindered by two problems nowadays.The first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of...The development of machine learning in complex system is hindered by two problems nowadays.The first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven algorithm.The second problem is the lack of a general theory which can be used to analyze and implement a complex learning system.In this paper,we proposed a general methods that can address both two issues.We combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by self-boosting.Formulating a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.展开更多
In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the...In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.展开更多
文摘本文旨在讨论智联网(Internet of minds,Io M)的基本概念,核心问题和关键平台技术.首先阐述智联网概念的智能时代发展需求和科学哲学思想基础,然后阐述智联网技术的背景、定义、实质,及其实现协同认知智能的目标,并举例说明其前沿应用领域,包括物理信息社会系统、软件定义系统及流程、工业智联网.接下来探讨智联网的核心问题:知识的获取、知识的协同表征和传递、以及知识的关联和协同运行.最后简单描述了智联网的关键平台技术,包括虚实平行的平台体系和基于互联网、物联网、区块链和软件定义网络的社会化通信计算平台,为分布式、自组织、自运行的安全智联网系统提供基础设施.
文摘动态网民群体(cyber-enabled social movement organizations,CeSMOs)将是近期信息、控制、智能科学等领域的研究焦点.本文简述CeSMOs的背景、现状、趋势和意义,并提出利用基于ACP概念的计算与平行系统方法来研究动态网民群体.通过人工组织对CeSMOs进行建模表示,采用计算实验对其进行分析评估,利用平行执行对其监控和管理.在此基础上,进一步探讨社会计算与平行系统的未来研究方向及方法.最后简要评述相关研究工作在产业发展中的可能作用及对社会演化的可能影响.
基金supported in part by the National Natural Science Foundation of China(91520301)
文摘The development of machine learning in complex system is hindered by two problems nowadays.The first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven algorithm.The second problem is the lack of a general theory which can be used to analyze and implement a complex learning system.In this paper,we proposed a general methods that can address both two issues.We combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by self-boosting.Formulating a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.
基金supported in part by the National Key Research and Development Program of China(2018AAA0101502,2018YFB1702300)the National Natural Science Foundation of China(61722312,61533019,U1811463,61533017)。
文摘In this paper,a new parallel controller is developed for continuous-time linear systems.The main contribution of the method is to establish a new parallel control law,where both state and control are considered as the input.The structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is presented.Considering the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are analyzed.The parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely controllable.Finally,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present method.Index Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.