电力系统工程设计文件代理人网络跨链技术

当前区块链跨链技术存在跨链监管存证更困难、新链接入过程不明确、异构链间数据结构转换复杂等问题。针对这些问题,将节点性能指标和身份评估、异构数据结构转换、点对点自组织网络等技术应用于工程文件数据跨链,提出代理人网络跨链方案。设计代理人节点选举算法,构建代理人跨链网络;明确工程文件数据跨链过程并记录工程文件跨链信息。仿真实验结果表明,该方案能完成工程文件数据跨链过程的实现。

沈阳国际公司建立国外业务代理人网络

沈阳国际经济技术合作公司根据国际承包劳务市场信息多变、竞争激烈的严峻形势,从基础工作抓起,利用多种渠道建立发展国外业务代理人网络,从而扩大了对外联系和交往,为参与国际竞争创造条件。

基于多代理人的企业集成

为适应制造系统中环境的动态变化 ,提出一种结合分布式控制和多代理人技术的企业集成方法 ,通过各级代理人之间的协商来解决制造系统的扩展性与自适应问题 ,给出了基于定单的多代理人协同方案 。

Controlled Remote State Preparation

We present a scheme for remotely preparing a state via the controls of many agents in a network.In thescheme,the agents' controls are achieved by utilizing quantum key distribution.Generally,the original state can berestored by the receiver with probability 1/2 if all the agents collaborate.However,for certain type of original states therestoration probability is unit.

Current Status of Intelligent Space

Latest advances in network sensor technology and state of the art of mobile robotics and artificial intelligence research can be applied to develop autonomous and distributed monitoring systems. Intelligent Space （iSpace） is an environmental system, which is able to support human in informative and physical ways. iSpace observing the space with distributed sensors, extracts useful information from the obtained data and provides various services to users. This means that essential functions of iSpace are ＂observation＂, ＂recognition＂ and ＂actuation.＂ In this paper, we focus on the observation function of iSpace. And we describe observation systems to get information of both human and mobile agents in the space to show new results.

Soft-Control for Collective Opinion of Weighted DeGroot Model

The DeGroot model is a classic model to study consensus of opinion in a group of individuals(agents). Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value? In this paper a mechanism named soft control is first introduced in opinion dynamics to guide the group's opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents,called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered: Adding a shill with an initial opinion value which is smaller(or larger) than the original convergent opinion value dose not necessarily decrease(or increase) the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.

Coupling Agent Based Simulation with Dynamic Networks Analysis to Study the Emergence of Mutual Knowledge as a Percolation Phenomenon

The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio-technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reproduced by multi-agent simulations. Whilst such simulations have been used to design real work settings the underlying theoretical grounding for the process is vague. The aim of this paper is to investigate whether the emergence of mutual knowledge(MK) in a group of colocated individuals can be explained as a percolation phenomenon. The followed methodology consists in coupling agent-based simulation with dynamic networks analysis to study information propagation phenomena: After using an agent-based simulation the authors generated and then analyzed its traces as networks where agents met and exchanged knowledge. Deep analysis of the resulting networks clearly shows that the emergence of MK is comparable to a percolation process. The authors specifically focus on how changes at the microscopic level in the proposed agent based simulator affect percolation and robustness. These results therefore provide theoretical basis for the analysis of social organizations.

Distributed Clustering Algorithm for Energy Efficiency and Load-Balance in Large-Scale Multi-Agent Systems

To improve the energy efficiency and load-balance in large-scale multi-agent systems, a large-scale distributed cluster algorithm is proposed. At first, a parameter describing the spatial distribution of agents is designed to assess the information spreading capability of an agent. Besides, a competition resolution mechanism is proposed to tackle the competition problem in large-scale multiagent systems. Thus, the proposed algorithm can balance the load, adjust the system network locally and dynamically, reduce system energy consumption. Finally, simulations are presented to demonstrate the superiority of the proposed algorithm.