基于联合意图理论的团队交互增强性原语语义研究

目前主流的主体通信语言FIPA ACL对于形成团队协作求解存在通信原语支持不充分的问题.首先指出基于全责提议通信原语的FIPA ACL不能充分支持团队协作的原因,进而明确区分全责提议与联合提议,引入语义成分扩展定义了联合提议.通过以联合提议原语形成的团队性质定理之验证,从理论上使团队在以联合提议形式进行联合意图交流时,团队主体间的协作能力得到改进.     

一种移动Agent通信协作模型

基于FIPA ACL和Linda协作模型的思想和方法，提出一种移动Agent通信协作模型Wagent模型。这种通信协作模型结合了FIPA ACL和Linda协作模型各自的优点，解决基于语义的协作和移动Agent的通信失效问题。在IBM的Aglet平台上，实现这种通信协作模型。     

基于请求／服务协作模型的多Agent建模方法

为了实现多Agent环境中主体之间的交互特性,在情景演算理论框架下研究了多Agent的通信动作,基于情景演算理论和Golog语言,介绍了ConGolog的语法和语义,并对Con Golog进行扩展。增加了并发处理,优先级的并发以及中断处理。在此基础上,提出一种基于请求,服务协作的多Agent模型,从而实现多Agent程序的并发交互执行。最后,通过对送咖啡例子的仿真,证明上述方法在实现虚拟场景中的多Agent协作行为方面是正确有效的。     

基于XML的Agent通信语言

Agent之间的交互与合作是Agent系统中核心问题之一，而Agent通信语言(ACL)是实现交互与合作的基础。根据目前Agent的应用环境，分析了目前主流通信语言KQML与FIPA ACL以及与之相关的内客语言的缺点，结合WWW的主流技术XML，提出基于XML的ACL。     

多Agent系统规划协作过程研究

在多Agent问题求解方面,一个明显的问题是如何规划Agent组的活动.多Agent规划是指通过Agent调整的行为朝着一个共同目标来增强系统中多个Agent协作的强度,从而提高系统的一致性.从协调一致性原理的角度来说明多Agent系统规划协作的过程,并将其划分为发现协作潜力、调解协作请求、构建协作团队、制订协作计划、实现协作行动及评估行动结果6个阶段,对各个阶段进行了说明.并对一种主从式层次结构的多Agent系统协作过程进行了阐述,构建了基于这种结构协作的基本模型.     

基于流演算的多Agent请求/服务协作模型的研究

为了刻画多Agent环境中的交互特性,基于流演算理论和GoFlux语言,吸收了ConGolog语义,提出了CFlux语言。CFlux语言能有效地处理MAS中的For循环、并发、优先级并发、中断等操作,从而可以实现多Agent程序的并发交互执行。在此基础上,基于CFlux和一组通信动作提出一个请求/服务协作模型。最后,通过一个智能日程安排实例表明了上述理论。     

基于多Agent的电子政务公文交换系统

公文交换是电子政务中的一个重要应用，本文阐述了一个符合FIPA规范的使用JADE框架的多Agent电子政务公文交换系统的设计。具体介绍了其组织结构、系统框架，目录服务的实现以及Agent间通信协作所使用的本体和交互协议。     

基于多Agent的复合模型求解自适应QoS机制

在基于网络的分布式系统应用基础上，分析了大型复杂问题复合模型协作求解的过程特征描述，提出基于多Agent 的领域问题协作求解的主动控制策略，探讨了用户交互Agent、系统主控Agent、协作Agent以及模型Agent和数据Agent等复合模型协作求解的4种Agent类型。应用多Agent层次结构，提出一种复合模型协作求解的自适应QoS体系结构，通过实现复合模型协作求解的主动调度规划算法对其进行了验证，支持分布式网络环境下实现模型资源和数据资源的共享，以提高协同计算环境分布式问题协作求解的运行效率和服务质量。     

基于着色Petri网的多Agent系统交互协议建模

多Agent系统(Multi-Agent Systems,MAS)中,多个Agent通过交互和协作来完成一系列任务或实现一些目标。Agent之间有效、有序地进行交互是MAS成功运行的关键。文中采用着色Petri网来表示一个多Agent系统。利用着色Petri网,便于描述并发现象和模拟平行系统,除了直观的图形化表示,还具有精确的形式化定义,并且有完善的分析工具。最后对FIPA规范中的FIPA Inform和FIPA Request两个协议进行实例分析,说明如何用着色Petri网进行建模。     

基于Agent的交通信息监控平台的设计

为了提高高速公路交通综合管理系统的可扩充性和可重用性,采用Agent技术设计基于Agent的交通信息监控平台,将交通系统中的各个模块封装成具有自主性、智能性和协作性的Agent,并确定了不同功能、不同层次的各Agent的内部结构.参照FIPA Agent,设计平台各Agent之间的通讯机制和协议,从而将不同功能、不同层次的Agent通过一定的协调机制有机地组成一个多Agent系统.     

Reliable Agent Communication — A pragmatic perspective

It is well recognized that Agent Communication Languages (ACL’s) are critical elements of Multi-Agent Systems and a key to their successful application in commerce and industry. The established field ofprotocol engineering, which concerns itself with how to specify machine communication languages and protocols, verify their properties and validate implementations thereof, has developed powerful, theoretical and practical techniques for doing so, and a mature understanding of the essential requirements that such specifications should meet. Regrettably, this body of knowledge and practice appears to have had little influence on recently proposed ACL standards. For example, the latest ACL specifications proposed by the Foundation for Intelligent Physical Agents (FIPA) are a confusing mix of different formal and informal specification techniques whose net result is ambiguous, inconsistent and under-specified. Allowances must be made, as these are still draft specifications, but rather than providing a verified foundation for reliable communication between heterogeneous agents, they run the risk of leading to unreliable or incompatible implementations, or of being ignored in favour of more pragmatic and robust approaches. In this paper, we propose a set of basic requirements which an ACL specification should meet, describe how the FIFA ACL measures up against these, and contrast its features with those of a small ACL which was designed with reliability and ease of verification as prime objectives. David Kinny: He is a Senior Research Fellow in the Intelligent Agent Laboratory of the Departments of Information Systems and Computer Science at the University of Melbourne, where he obtained his B. Sc. (Hons) in Computer Science in 1991. He then became Research Manager at the Australian Artificial Intelligence Institute, where he designed several influential advanced agent technologies including the dMARS system. His research focus is on Agent Architectures, Agent Communication Languages, and formal semantics for Agent Programming Languages. He is the author of 11 research papers on Software Agents, has served on the program and steering committees of several agent conferences, and is moderator of the Usenet newsgroup <compai>.     

The State of the Art in Agent Communication Languages

Like societies of humans, there is a need for agents in a multi-agent system to rely on one another, enlist the support of peers in order to solve complex tasks. Agents will be able to cooperate only through a meaningful communication language that can bear correctly their mental states and convey precisely the content of their messages. In search for the ideal agent communication language (ACL), several initiatives like the pioneering work of the Knowledge Sharing Effort and the Foundation for Intelligent Physical Agents (FIPA) are paving the way for a platform where all agents would be able to interact regardless of their implementation environment. ACL is a new field of study that could gain from a survey in expanding its application areas. For this purpose, we examine in this paper the state of the art in ACL design and suggest some principles for building a generalized ACL framework. We then evaluate some existing ACL models, and present the current issues in ACL research, and new perspectives. Received 22 July 1999 / Revised 23 March 2000 / Accepted 2 May 2000     

基于多Agent拍卖的网格资源主动分配

为了保障网格资源的利用率和实现资源主动分配,提出基于FIPA（Foundation of Intelligent Physi-cal Agents）英式拍卖和荷兰式拍卖协议的网格资源分配方法,在多Agent开发平台JADE（Java Agent Develop-ment Framework）下分别对这两种拍卖协议作了实现,给出了具体的实现算法、步骤、参与拍卖的各Agent的交互过程以及拍卖结果。最后,用实例说明了仿真实现过程的正确性。     

基于多Agent拍卖的网格资源主动分配

为了保障网格资源的利用率和实现资源主动分配,提出基于FIPA（FoundationofIntelligentPhysi-calAgents）英式拍卖和荷兰式拍卖协议的网格资源分配方法,在多Agent开发平台JADE（JavaAgentDevelop-mentFramework）下分别对这两种拍卖协议作了实现,给出了具体的实现算法、步骤、参与拍卖的各Agent的交互过程以及拍卖结果。最后,用实例说明了仿真实现过程的正确性。     

Some Remarks on the Semantics of FIPA's Agent Communication Language

The Foundation for Intelligent Physical Agents (FIPA) standardisation body has produced a set of specifications outlining a generic model for the architecture and operation of agent-based systems. The FIPA'97 Specification Part 2 is the normative specification of an Agent Communication Language (ACL) which agents use to talk to each other. The FIPA ACL is based on speech act theory. Its syntax is defined by performatives parameterised by attribute value pairs, while its semantics is given in terms of the mental states of the communicating agents (i.e. intentionality). However, it is not clear if the formal semantics is meant as a normative or informative specification. The primary purpose of this paper is then to give an expository analysis of the FIPA ACL semantics to clarify this situation. We also offer some guidelines motivated from our own analysis, experience and understanding of how the semantic definitions and logical axioms should be interpreted and applied. However, our conclusion is that while the FIPA ACL specification offers significant potential to a developer using it for guidance, there are limitations on using an agent's mental state to specify the meaning of a performative as part of a normative standard. We consider some possibilities for making improvements in this direction.     

Trends in Agent Communication Language

Agent technology is an exciting and important new way to create complex software systems. Agents blend many of the traditional properties of AI programs—knowledge–level reasoning, flexibility, proactiveness, goal–directedness, and so forth—with insights gained from distributed software engineering, machine learning, negotiation and teamwork theory, and the social sciences. An important part of the agent approach is the principle that agents (like humans) can function more effectively in groups that are characterized by cooperation and division of labor. Agent programs are designed to autonomously collaborate with each other in order to satisfy both their internal goals and the shared external demands generated by virtue of their participation in agent societies. This type of collaboration depends on a sophisticated system of inter–agent communication. The assumption that inter–agent communication is best handled through the explicit use of an agent communication language (ACL) underlies each of the articles in this special issue. In this introductory article, we will supply a brief background and introduction to the main topics in agent communication.