电子商务环境中一种基于多主体系统的信任模型

为了解决电子商务环境的动态性和不确定性带来的信任问题,提出一种基于多主体系统的信任模型来处理电子商务环境中Agent之间的信任关系。与现有的信任模型相比,该模型能自主处理Agent间的欺诈信息,同时在估价Agent的信任关系时引入了时间退化因子。模拟实验表明,时间退化因子和信任的精确度即信心的引入,能更加有效地评估Agent之间的信任关系。此外,模型中引入了信任的本体性概念。     

论辩系统的动态性及其研究进展

论辩系统是一种非单调形式体系,能够支持个体Agent的推理决策和多Agent之间的有效交互.由于个体Agent的知识、观察信息和资源的动态性以及多Agent交互过程的动态性,在各类论辩系统中,论证及其攻击关系的动态性是普遍存在的.作为一个新的研究领域,有关论辩系统动态性的概念、理论和方法远未成熟.在介绍论辩系统相关概念的基础上,阐明论辩系统动态性的两个主要研究方向(正向动态性和逆向动态性),并讨论需要解决的开放性问题.围绕这些问题,简要回顾现有的理论和方法,并分析其特点和不足.     

MAS中一种基于概率论的信任模型

信任是多主体系统（MAS）研究的一个热点问题。为了解决MAS的动态性和不确定性带来的信任问题,提出了一种基于概率论的信任模型。与现有的信任模型相比,该模型考虑了信任信息的完整性和信任的动态性：即在估价agent的信任关系时引入了信任的精确度信心和时间退化因子。模拟实验表明,时间退化因子和信心的引入,能更加有效地评估agent之间的信任关系。     

基于Agent的分布式系统信任模型仿真

针对当前信任模型仿真缺乏理论支撑,仿真过程描述及建模步骤不规范的问题,将多Agent建模仿真方法应用于信任模型的仿真,建立信任模型Agent仿真过程框架.由信任模型微观机制入手,对个体Agent进行设计,建立Agent实体模型;针对信任模型中Agent之间的交互问题设计基于推荐网的Agent协作算法;在充分考虑系统宏观约束的情况下,建立微观Agent到宏观系统之间的联系.通过实例验证了该方法的有效性.     

基于多Agent的网格信任模型

在对相关信任模型研究的基础上,提出了一个基于多Agent的信任模型,该模型采用在每个管理域设置多个Agent,每个实体和多个Agent关联的方式来管理网格环境中实体间的信任关系.实验和分析结果表明,与其它基于声誉的信任模型相比,这种模型不但缩短了交易响应时间,而且提高了作业成功率,从而能更加有效地解决网格环境中存在的安全问题.     

基于组织的面向Agent 程序设计及其语言Oragent

当前,面向Agent程序设计在支持动态开放多Agent系统开发方面存在一系列的不足,如缺乏高层抽象、底层实现模型与高层设计模型相脱节、在支持系统动态性方面缺乏有效的运行机制和语言设施等.针对这些问题,提出一种基于组织的面向Agent程序设计方法.该方法将组织、Group、角色和Agent等高层抽象作为一阶实体,缩小了多Agent系统的设计模型与实现模型之间的概念鸿沟;借助于组织学中的机制——角色扮演机制、基于角色的交互——支持系统动态性的规约和实现,如Agent行为的动态组合、动态的交互等,基于该程序设计思想,设计了基于组织的面向Agent程序设计语言——Oragent,定义了其抽象语法和形式语义,并通过案例分析说明了如何基于该程序设计思想和Oragent语言来构造和实现动态而灵活的多Agent系统.     

基于可信计算的网格行为信任模型研究

网格环境中的信任问题是网格计算发展过程中必须解决的一个重要问题。网格实体间的信任可以分为身份信任和行为信任两种，其中行为信任关注的是更广泛意义上的可信性问题，具有动态性和不确定性等特点，实体可以根据彼此之间的交互经验动态更新实体间的信任关系。而可信计算技术是为应对计算机安全问题而提出的一种底层的、整体的解决方案。该文以可信计算平台为基础，提出了一种网格环境中的行为信任模型，并对行为信任进行量化评估，最后对该模型中的几个关键问题进行了分析。     

基于多Agent的医疗信任模型的模拟

结合直接交互信任评价和第三方信誉推荐,提出了一种基于多Agent技术的医疗信任模拟模型。使用置信因子来综合直接交互信任值和第三方信誉推荐值;避免了患者直接交互的盲目性和巨额计算,完善了对医生自我推荐的辨别能力。实验采用Swarm仿真平台模拟医疗信任模型的交互过程,结果表明该模型在确定信任关系中相对IT模型要快,比第三方信誉推荐模型相对要可靠。     

开放多Agent系统的一个信任信誉系统模型

信任和信誉对于开放多Agent系统的有效交互是十分重要的.FIRE模型是最近提出的适用于开放环境下问题求解的信任信誉系统模型中的一种,在该模型中没有考虑消费者的个性特征,从而使得消费者给出的评分仅直接反映了提供者的服务质量,这就减弱了该模型的实用价值.提出了扩展模型E-FIRE,引入了消费者的个性特征.其个性特征包括两个方面:消费者对服务质量的预期和消费者采取的态度.这两方面共同影响消费者对待同一服务的评分.因此,消费者的评分不再只反映提供者的服务质量,这样使得该模型更加符合实际情况.同时,在消费者为选择提供者而计算提供者的综合信任评分时,更多地依靠提供证据的消费者对提供者的直接信任,从而减少了Agent 间的通信量.实验结果表明,在交互次数较少时,E-FIRE模型的性能与FIRE模型的性能相当;随着交互次数的增多,E-FIRE模型的性能更优.     

普适环境中基于模糊理论的信任评估模型

信任管理是当前普适环境中信息安全研究的热点。为了解决主观信任的模糊性和主体之间信任关系的动态性,在模糊数学中的模糊理论的基础上,提出了一个用户信任度的评估模型。该模型是将模糊理论应用到信任关系的不确定性和动态性上,对影响信任主体的主要因素进行综合评估,得出一个总的信任度来确定是否可以信任主体以便进行交互。该模型可以全面地评估用户的信任度,很大程度上保证了普适行为的安全可靠,为处理普适计算的信任管理的不确定研究提供了一个新的方法。     

强化学习与自适应动态规划:从基础理论到多智能体系统中的应用进展综述

近年来,强化学习与自适应动态规划算法的迅猛发展及其在一系列挑战性问题(如大规模多智能体系统优化决策和最优协调控制问题)中的成功应用,使其逐渐成为人工智能、系统与控制和应用数学等领域的研究热点.鉴于此,首先简要介绍强化学习和自适应动态规划算法的基础知识和核心思想,在此基础上综述两类密切相关的算法在不同研究领域的发展历程,着重介绍其从应用于单个智能体(控制对象)序贯决策(最优控制)问题到多智能体系统序贯决策(最优协调控制)问题的发展脉络和研究进展.进一步,在简要介绍自适应动态规划算法的结构变化历程和由基于模型的离线规划到无模型的在线学习发展演进的基础上,综述自适应动态规划算法在多智能体系统最优协调控制问题中的研究进展.最后,给出多智能体强化学习算法和利用自适应动态规划求解多智能体系统最优协调控制问题研究中值得关注的一些挑战性课题.     

Topological analysis of AOCD-based agent networks and experimental results

Topological analysis of intelligent agent networks provides crucial information about the structure of agent distribution over a network. Performance analysis of agent network topologies helps multi-agent system developers to understand the impact of topology on system efficiency and effectiveness. Appropriate topology analysis enables the adoption of suitable frameworks for specific multi-agent systems. In this paper, we systematically classify agent network topologies and propose a novel hybrid topology for distributed multi-agent systems. We compare the performance of this topology with two other common agent network topologies—centralised and decentralised topologies—within a new multi-agent framework, called Agent-based Open Connectivity for DSS (AOCD). Three major aspects are studied for estimating topology performance, which include (i) transmission time for a set of requests; (ii) waiting time for processing requests; and (iii) memory consumption for storing agent information. We also conduct a set of AOCD topological experiments to compare the performance of hybrid and centralised agent network topologies and illustrate our experimental results in this paper.     

一个软件服务协同中的信任管理框架设计

Internet-based Web application systems are gradually built as software service coordination systems. In an open, dynamic and collaborative application environment, traditional methods assumed with closeness, centralization and independence are not able to cope with these security problems efficiently. Trust management is a new method for dealing with security issues of open, distributed network application system. However, the traditional policy-based trust management systems have some shortcomings, i.e. complex in policy making, unable to deal with negative se-curity credentials, etc. So, we design a trust management framework in combination with subjective trust model for software service coordination and security decision in Internet environment. This trust management framework has characteristics of operability, reasonability, and flexibility in policy setting.     

Attribute-based authentication for multi-agent systems with dynamic groups

In a multi-agent system, agents are required to interact in order to exchange information. To achieve a reliable information exchange, a sound security protection must be in place. Unfortunately, security and privacy in multi-agent systems have not drawn adequate attention. They have been actually ignored or mistreated in most proposed multi-agent protocols. We observe that security and privacy issues are indeed not trivial and cannot be resolved with traditional security mechanisms, if agents are not trusted each other and their privacy must be protected. In this paper, we propose a secure multi-agent protocol that captures several most important security properties including agent privacy, data confidentiality, and agent authenticity. Intuitionally, we allow each agent in a group to hold a set of policy attributes. To access a protected data set, an agent must hold a correct policy attribute. In other words, the private information between two agents can be exchanged, if and only if the policy attribute embedded in the transmitted message matches that held by the receiver. In case of mismatching attributes, the private information of the corresponding agent will not be revealed to their counterpart. The proposed scheme is formalized with a sound cryptographic algorithm with a rigorous security proof.     

Agent动态交互信任预测与行为异常检测模型

在agent理论中,信任计算是一个有意义的研究方向.然而目前agent信任研究都是以平均交互成功率来计算,较少考虑信任动态变化,因而准确预测和行为异常检测的能力不能令人满意.针对上述问题,以概率论为工具,按时间分段交互历史给出agent交互信任计算模型CMAIT;结合信任的变化率,给出信任计算的置信度和异常检测机制.实验以网上电子商务为背景,实验结果显示该计算模型的预测误差为TRAVOS的0.5倍,计算量也较少;既可用于对手历史行为的异常检测,防止被欺骗,又可用于对手未来行为的预测.改进了Jennings等人关于agent信任的工作.     

Consensus of multi-agent systems under switching agent dynamics and jumping network topologies

Consensus of multi-agent systems is an interesting research topic and has wide applications in science and engineering. The agents considered in most existing studies on consensus problem are time-invariant. However, in many cases, agent dynamics often show the characteristic of switching during the process of consensus. This paper considers consensus problem of general linear multi-agent system under both switching agent dynamics and jumping network topologies. Within the proposed multi-agent system, the agent dynamic switching is assumed to be deterministic, while the network topology jumping is considered respectively for two cases: deterministic jumping (Case 1) and Markov jumping (Case 2). By applying the dwell time and the average dwell time techniques, a sufficient consensus and an almost sure consensus conditions are provided for these two cases, respectively. Finally, two numerical examples are presented to demonstrate the theoretical results.     

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology, a networked multi-agent control system is a key direction of modern industrial control systems, such as industrial Internet systems. This paper studies the tracking control problem of networked multi-agent systems with communication constraints, where each agent has no information on the dynamics of other agents except their outputs. A networked predictive proportional integral derivative(PPID) tracking scheme is proposed t...     

单向通信拓扑领航者动态未知线性多智能体系统的协同迭代学习控制（英文）

This paper considers the cooperative tracking of linear multi-agent systems with a dynamic leader whose input information is unavailable to any followers. Cooperative iterative learning controllers, based on the relative state information of neighboring agents, are proposed for tracking the dynamic leader over directed communication topologies. Stability and convergence of the proposed controllers are established using Lyapunov-Krasovskii functionals. Furthermore, this result is extended to the output feedback case where only the output information of each agent can be obtained. A local observer is constructed to estimate the unmeasurable states. Then, cooperative iterative learning controllers, based on the relative observed states of neighboring agents,are devised. For both cases, it is shown that the multi-agent systems whose communication topologies contain a spanning tree can reach synchronization with the dynamic leader, and meanwhile identify the unknown input of the dynamic leader using distributed iterative learning laws. An illustrative example is provided to verify the proposed control schemes.     

单向通信拓扑领航者动态未知线性多智能体系统的协同迭代学习控制

研究单向通信拓扑领航者动态未知线性多智能体系统的协同跟踪问题.基于邻居的相对状态信息,设计了分布式迭代学习控制律实现对领航者的协同跟踪控制,采用Lyapunov-Krasovskii函数分析闭环系统的稳定性与收敛性.进而,将状态反馈结论拓展到输出反馈,通过构造局部观测器估计不可量测的状态信息,采用估计的相对状态信息设计了分布式迭代学习控制器.对于以上两种情形,多智能体系统在通讯拓扑含有生成树的条件下能够实现与领航者的状态同步,同时,所设计的分布式迭代学习律能够对领航者未知输入进行精确估计.仿真实例验证了所提方法的有效性.