PTS领域中的Agent体系结构设计与实现

目前大部分的多Agent系统协作理论没有对实时、动态和通信不可靠环境下的Agent体系结构给出合适的解决方案。该文首先给出了对动态、实时和通信不可靠环境下的多Agent协作问题的一种典型描述──PTS领域的定义,并分析了PTS领域的消息处理及动作执行的循环机制。在此基础上,给出了适合于PTS领域的Agent体系结构,最后在微机平台上用面向对象的方法以机器人足球仿真比赛为背景实现了这种体系结构。     

自主移动机器人混合式体系结构的设计与实现

针对以往自主移动机器人体系结构在实时处理方面的不足,提出了一种基于多智能体的混合式体系结构,统一规划了机器人系统的软硬件结构,在该体系结构中设计并实现了协调Agent和推理Agent两种智能体,针对紧急事件进行了更实时的Agent实现,有效的提高的自主移动机器人在突发事件时的实时性,提出了使用多样化的信息组织形式,增强了系统的自适应能力和易扩展性。本文的实验结果表明在紧急状态下,系统的反应时间有效缩短,增加了系统的智能性和实时性。     

基于MAS智能分布实时监测系统任务协调与调度

在现代分布实时监测系统工作环境下,要清晰地表示分布的任务结构和任务之间的交互关系是非常困难的。为了解决这个问题,给出了一种Agent体系结构,它通过一般部分全局计划方法表示Agent任务结构,实现具有一定适应能力的协调机制,获得Agent本地调度方案。     

面向群体协同飞行作战的分布实时多Agent系统研究

针对飞行作战环境的复杂性,即飞行作战系统的多任务、高实时性、协调性等特点,提出了基于分布实时多A-gent的飞行作战知识处理系统体系结构,通过分析飞行作战系统特有的高实时性要求,对分布实时多Agent系统的通信机制、协调机制等进行了研究,给出了基于时间约束的多Agent系统的技术解决方案。     

Agent技术在Web数据仓库结构中的应用研究

针对基于Web的数据仓库体系结构存在的问题,在该体系结构中引入软件Agent技术,运用移动Agent技术来解决传统方法难以解决的一些主要问题,提出了一种基于Agent的Web数据仓库系统体系结构。文中发挥数据仓库技术和Web技术结合的优势,重点研究了Agent技术在Web服务器端的应用,在把有用的Web数据集成并入到数据仓库中这一目前的研究热点问题中,提出了基于Agent技术将HTML页面转化为XML数据源的解决方案。此外,文章分别研究了应用服务器端和数据仓库系统中的Agent技术的应用,并提出了将Agent技术引入后实现基于Web的数据仓库体系的关键技术。     

通用的移动Agent系统快速集成开发环境

在研究多种Agent系统的体系结构的基础上给出通用的多Agent系统平台和移动Agent的体系结构,并在开源的JADE上实现了一个通用的移动Agent系统快速集成开发环境原型,采用“Framework-plugin”和分层的设计模式,通过对配置文件的动态加载可以快速灵活地建造适用不同要求和具有不同属性的移动Agent系统。     

变电站智能诊断和维护系统体系结构研究

采用多Agent技术对变电站智能诊断和维护系统的体系结构进行了研究。在此基础上给出了基于多Agent的变电站智能诊断和维护系统体系结构模型,构建了该模型下各层Agent的体系结构,并对各层Agent的功能、协调控制机制和系统工作原理进行了说明,最后在研究结果的基础上,提出后续研究需要考虑的问题,为变电站智能诊断和维护系统的研究和开发提供了参考和思路。     

Multi-Agent系统在主动网络管理中的应用研究*

将分布式人工智能中的智能Agent用于计算机网络管理,是近年来最活跃最前沿的研究领域之一。介绍Agent和多Agent系统(MAS)以及主动网络的概念,从分布式主动网络管理体系结构入手,论述了基于多Agent的主动网络管理模型,研究了主动网络管理智能Agent以及MAS体系结构。     

Agent的体系结构

首先介绍了Agent的基本概念,然后针对BDI Agent和移动Agent,讨论Agent的体系结构。     

一种新的基于Agent的体系结构

Agent体系结构是由理论研究向系统实现的关键一步。首先,在Agent特性分析和形式化描述的基础上,阐述了Agent的层次概念框架。然后,研究SubSumption,BDI和GRATE等典型结构特点,比较了反应式和慎思式两种体系结构,反应式Agent和慎思式Agent体系结构各有优劣。确立采用分层式混合结构的设计思想,并结合Agent的特性,从信息流和控制流的角度来刻画更为复杂的层次结构。在此基础上,设计了一种带序列池（POOL）的二维混合体系结构,并对其实现机制进行了深入研究。在不增加系统复杂性的前提下,提高系统的效率和能力。     

A real-time architecture for time-aware agents

This paper describes the specification and implementation of a new three-layer time-aware agent architecture. This architecture is designed for applications and environments where societies of humans and agents play equally active roles, but interact and operate in completely different time frames. The architecture consists of three layers: the April real-time run-time (ART) layer, the time aware layer (TAL), and the application agents layer (AAL). The ART layer forms the underlying real-time agent platform. An original online, real-time, dynamic priority-based scheduling algorithm is described for scheduling the computation time of agent processes, and it is shown that the algorithm's O(n) complexity and scalable performance are sufficient for application in real-time domains. The TAL layer forms an abstraction layer through which human and agent interactions are temporally unified, that is, handled in a common way irrespective of their temporal representation and scale. A novel O(n2) interaction scheduling algorithm is described for predicting and guaranteeing interactions' initiation and completion times. The time-aware predicting component of a workflow management system is also presented as an instance of the AAL layer. The described time-aware architecture addresses two key challenges in enabling agents to be effectively configured and applied in environments where humans and agents play equally active roles. It provides flexibility and adaptability in its real-time mechanisms while placing them under direct agent control, and it temporally unifies human and agent interactions.     

动态不确定环境下的决策：一种分层决策模型

本文提出一种智能体分层决策结构模型，试图通过分层决策技术有效地解决动态、不确定环境中的智能体的实时决策问题。本模型的高层采用BDI结构，以便为较长期任务的规划和推理提供充分的支持；模型的底层采用反应式结构，以保证对短期实时任务的及时响应。实验结果表明了这种分层模型在某些复杂任务领域中的有效性。     

ON THE ROLE OF BDI MODELING FOR INTEGRATED CONTROL AND COORDINATED BEHAVIOR IN AUTONOMOUS AGENTS

This paper describes an architecture for controlling and coordinating autonomous agents, building on previous work addressing reactive and deliberative control methods. The proposed multilayered hybrid architecture allows a rationally bounded, goal-directed agent to reason predictively about potential conflicts by constructing knowledge level models that explain other agents' observed behaviors and hypothesize their beliefs, desires, and intentions; at the same time, it enables the agent to operate autonomously, to react promptly to changes in its real-time environment, and to coordinate its actions effectively with other agents. A principal aim of this research is to understand the role dzfferent functional capabilities play in constraining an agent5 behavior under varying environmental conditions. To this end, an experimental test bed has been constructed comprising a simulated multi-agent world in which a variety of agent configurations and behaviors have been investigated. A number of experimentalfindings are reported.     

一种适用于Internet的实时多Agent系统模型

提出了一种基于Agent to Agent架构的,适用于Internet环境的实时多Agent系统模型。重点阐述了该模型中Agent之间的协作方式、调度策略和任务执行的控制策略,并介绍了采用的实时Agent通信语言和通信机制。     

Reflections on the Nature of Multi-Agent Coordination and Its Implications for an Agent Architecture

The development of enabling infrastructure for the next generation of multi-agent systems consisting of large numbers of agents and operating in open environments is one of the key challenges for the multi-agent community.Current infrastructure support does not materially assist in the development of sophisticated agent coordination strategies. It is the need for and the development of such a high-level support structure that will be the focus of this paper. A domain-independent (generic) agent architecture is proposed that wraps around an agent's problem-solving component in order to make problem solving responsive to real-time constraints, available network resources, and the need to coordinate—both in the large and small—with problem-solving activities of other agents. This architecture contains five components, local agent scheduling, multi-agent coordination, organizational design, detection and diagnosis, and on-line learning, that are designed to interact so that a range of different situation-specific coordination strategies can be implemented and adapted as the situation evolves. The presentation of this architecture is followed by a more detailed discussion on the interaction among these components and the research questions that need to be answered to understand the appropriateness of this architecture for the next generation of multi-agent systems.     

一种基于行为的双层动态智能体结构及其在RoboCup中的应用

该文针对目前智能体结构模型的问题,提出了一种基于行为的双层动态智能体结构模型,它是一种混合结构模型,包括有反应式结构和慎思结构,并采用自信度来连接这两种结构,既可以提高在实时动态环境下智能体反应的敏捷性,也使自主机器人能够在动态环境下识别任务。这种混合结构模式已成功地应用于RoboCup仿真机器人足球赛中,并取得了比较好的成绩。     

A deliberative scheduling technique for a real-time agent architecture

In this paper, we present a heuristic to schedule complex task models (tasks that use Artificial Intelligence methods). These tasks are used in a real-time agent architecture called ARTIS. This architecture has been designed to build intelligent agents that work in hard real-time environments. To do this, the architecture provides scheduling at two levels. The first level assures the fulfilment of the hard temporal requirements, and the second level obtains a result of higher quality. The new heuristic, Slack-Slide Scheduling (SSS), works at the second level. It manages two types of methods: progressive refinement methods and multiple methods. The Slack-Slide Scheduling also attempts to reuse previous results in order to make better use of the existing CPU time while the first-level scheduler fulfils the deadlines.     

An architecture for real-time distributed artificial intelligent systems

This paper introduces a new architecture for a real-time distributed artificial intelligence system: DENIS—a Dynamic Embedded Noticeboard Information System. The fundamental idea underlying the architecture draws heavily upon a distributed human system analogy, as seen, for example, in the workplace. The aim of DENIS is to provide a simple, meaningful means by which autonomous intelligent agents can cooperate and coordinate their actions in order to enhance the reliability and effectiveness of a real-time distributed control system. Based on a human paradigm, the architecture inherently allows for the control of an intelligent agent to be taken over by a human operator, yet still to maintain consistency in the distributed system. The key to the thinking in this new approach is to try to model how humans work together, and to implement this in a distributed architecture. One of the main issues raised is that humans owe much of their flexibility to their ability to reason, not only logically, but also in terms of time.     

Addressing real-time constraints in the design of autonomous agents

The Phoenix project is an experiment in the design of autonomous agents for a complex environment. The project consists of a simulator of the environment, a basic agent architecture, and specific implementation of agents based on real-time techniques; the first two parts have been constructed, the third is on-going. The facets of Phoenix that facilitate real-time research are: a simulator parameterized for varying environmental conditions and instrumented to record behaviors, an agent architecture designed to support adaptable planning and scheduling, and methods for reasoning about real-time constraints.This research has been supported by DARPA, # F30602-85-C-0014; the Office of Naval Research, under a University Research Initiative grant, N00014-86-K-0764; the Office of Naval Research, # N00014-88-K0009, and a grant from the Digital Equipment Corporation. We wish to thank Mike Greenberg for his keen understanding of design issues and mastery of programming that made Phoenix what it is today. We also wish to thank Paul Silvey and David Westbrook for their help.     

实时环境下Agent决策机制研究

随着实时应用的日益广泛，越来越复杂的技术已经被应用到实时系统中．在分析已有Agent模型的基础上，提出了一种新的实时Agent模型．这种模型将Agent的审慎型行为和反应型行为结合在一起，其效率比已有的Agent模型有较大的提高．还讨论了实时Agent的决策机制，提出用感知器算法对特征进行分类和任意时间算法进行决策．