一种适合EAI的多Agent系统模型

企业应用集成是当前研究的热点，应用集成是能够满足企业统一信息管理、统一资源调配和优化业务流程的重要手段。目前应用集成尚无公认的标准，在实施集成中主要考虑标准接口问题，而往往忽略本身体系结构的合理性。要满足企业为适应市场竞争而灵活变动的管理模式，应用集成必须具备较高的可扩展性和可灵活调整性。在分析企业应用集成内涵的基础上，提出了适合于企业应用集成特点的多Agent系统模型。     

基于计算机审计的多Agent系统体系架构

提出了一种基于计算机审计的多Agent系统体系架构,分析了该结构中各子系统的组成 及各Agent功能特点。介绍了系统中移动审计Agent和移动Agent服务器设计实现。原型系统能够 实现实时分布在线计算机审计,表明该体系架构是切实可行的。     

On-board control in the RoboCup small robots league

We present the most recent version of our RoboCube system, a special robot controller hand-tailored for players in the small robots league. The RoboCube is conceptualized to implement players with as many on-board features as possible in an extremely flexible way. For this purpose, the RoboCube provides significant computation power and memory as well as a multitude of I/O interfaces within the space constraints. As it facilitates the use of many sensors and effectors, including their on-board processing, the RoboCube allows us to explore a large number of different robots and team set-ups.     

A multi-agent model system for land-use change simulation

This paper presents a multi-agent model system to characterize land-use change dynamics. The replicable parameterization process should be useful to the development of simulation frameworks, important to environmental policy makers to analyze different scenarios during decision making process. The methodological two-fold approach intends to form a solid backbone based on: (i) the systematic and structured empirical characterization of the model; and (ii) the conceptual structure definition according to the agent-based model documentation protocol – Overview, Design concepts and Details. A multi-agent system for land-use change simulation was developed to validate the model, which is illustrated with a case study of the Brazilian Cerrado using LANDSAT ETM images. The simulation results prove the model importance with a figure of merit greater than 50%, what means the amount of correctly predicted change is larger than the sum of any type of error. The results are very good compared with nine popular peer-reviewed land change models.     

Three years of the RoboCup standard platform league drop-in player competition

The Standard Platform League is one of the main competitions at the annual RoboCup world championships. In this competition, teams of five humanoid robots play soccer against each other. In 2013, the league began a new competition which serves as a testbed for cooperation without pre-coordination: the Drop-in Player Competition. Instead of homogeneous robot teams that are each programmed by the same people and hence implicitly pre-coordinated, this competition features ad hoc teams, i.e. teams that consist of robots originating from different RoboCup teams and as such running different software. In this article, we provide an overview of this competition, including its motivation, rules, and how these rules have changed across three iterations of the competition. We then present and analyze the strategies utilized by various drop-in players as well as the results of the first three competitions before suggesting improvements for future competitive evaluations of ad hoc teamwork. To the best of our knowledge, these three competitions are the largest annual ad hoc teamwork robotic experiment to date. Across three years, the competition has seen 56 entries from 30 different organizations and consisted of 510 min of game time that resulted in approximately 85 robot hours.     

Service-oriented architecture for ontologies supporting multi-agent system negotiations in virtual enterprise

This paper offers a service-oriented architecture (SOA) for ontology-based multi-agent system (MAS) negotiations in the context of virtual enterprises (VEs). The objective of this paper is fourfold. First, it is to design a SOA which utilizes ontology and MAS to provide a distributed and interoperable environment for automated negotiations in VE. In this architecture, individual ontologies for both the VE initiator and its potential partners are constructed to describe and store resources and service knowledge. Second, a series of semantic ontology matching methods are developed to reach agents’ interoperability during the negotiation process. Third, correspondence-based extended contract net protocol is presented, which provides basic guidelines for agents’ reaching mutual understandings and service negotiation. Last, a fuzzy set theory based knowledge reuse approach is proposed to evaluate the current negotiation behaviors of the VE partners. A walkthrough example is presented to illustrate the methodologies and system architecture proposed in this paper.     

A hybrid multi-agent system architecture for enterprise integration using computer networks

The manufacturing industries are now experiencing fierce pressure of competition from every corner on this planet. In addition, the advancement in computer networks and information technologies has been gradually reshaping the manufacturing companies by shifting from the industrial age to the information era. Due to these elevated competitiveness and advanced computer technology, a number of new manufacturing and management strategies (e.g., CE or CIM) have emerged for the innovation of manufacturing enterprises. Although they have different definitions and scopes, there are several common issues: inter-enterprise functions integration; inter-enterprise resources integration; and collaboration. This paper proposes a new multi-agent system (MAS) architecture to support the inter-enterprise functions/resources integration and collaboration over the networked environment, including the hybrid agent architecture and hybrid network architecture. In contrast to the existing agent architectures, the proposed agent architecture enables agents to exhibit the hybrid (continuous and discrete) behavior and interactions. In addition, our network architecture is more suitable for building the large-scale distributed manufacturing systems that are prone to dynamic random changes of their environment. Based on the proposed MAS architecture, a collaborative product development environment is implemented as a starting point, and a multidisciplinary team-oriented design problem is illustrated to provide the vision of the proposed MAS architecture.     

A re-configurable multi-agent system architecture for error recovery in production systems

Multi-agent systems for manufacturing systems appear to provide adequate response to abrupt disturbances on the shop floor. To date, most of the work has been focused on planning and scheduling but very little work has been done on issues pertaining to monitoring, diagnostics and error recovery. Our approach addresses the issue of combining the discipline of hierarchical systems with the agility of multi-agent systems. Within the context of a hierarchy, the focus is on the workstation level and, in particular, the construction of a re-configurable system having production agents, error recovery agents, and a mediator agent structure connecting production and recovery agent hierarchies. In addition, the relationship to a multi-level, multi-layer hierarchy control is established. This latter hierarchy, based on Petri Net constructs, serves, in one sense, as a retrieval based resource for process planning and generation of recovery plans for production and recovery agents within the proposed multi-agent system. An objective of this effort is to provide a test-bed for comparison of hierarchical systems, heterarchical, and a hybrid combination which is the focus of the investigation presented here.     

A new system architecture for crowd simulation

Crowd simulation requires both rendering visually plausible images and managing the behavior of autonomous agents. Therefore, these applications need an efficient design that allows them to simultaneously handle these two requirements. Although several proposals have focused on the software architectures for these systems, no proposals have focused on the computer systems supporting them.In this paper, we analyze the computer architectures used in the literature to support distributed virtual environments. Also, we propose a distributed computer architecture which is efficient enough to support simulations of thousand of autonomous agents. This proposal consists of a cluster of interconnected computers in order to improve flexibility and robustness, as well as a hierarchical software architecture that efficiently provides consistency. Performance evaluation results show that the trade-off between flexibility and consistency allows to efficiently manage thousands of autonomous agents. Therefore, this network-based system architecture can provide the required scalability for large-scale crowd simulations.     

A multi-agent architecture for control of AGV systems

Agent is an autonomous, computational entity that can be viewed as perceiving its environment and acting upon it. Agents are event-driven objects that can be integrated in automated manufacturing environments to control certain tasks. In this paper a set of agents (a multi-agent system) is introduced to control an automated manufacturing environment. The architecture includes functions at the manufacturing cell level, materials handling and transport level, and factory scheduling level. Communication between these agents is accomplished by using a relational database (blackboard system). The relational database also integrates the requirements of a manufacturing execution system within the multi-agent task structure, which is unique to this architecture. Manufacturing cell and scheduling agents have been previously described in the literature. Here we focus our attention on the functions of the agents of the transport system, which is composed of a set of AGVs.     

Using multi-agent architecture in FMS for dynamic scheduling

The proposed scheduling strategy is based on a multi-agent architecture. Each agent of this architecture is dedicated to a work centre (i.e. a set of resources of the manufacturing system); it selects locally and dynamically the most suitable dispatching rules. Depending on local and global considerations, a new selection is carried out each time a predefined event occurs (for example, a machine becomes available, or a machine breaks down). The selection depends on: (1) primary and secondary performance objectives, (2) the operating conditions, and (3) an analysis of the system state, which aims to detect particular symptoms from the values of certain system variables. We explain how the scheduling strategy is shared out between agents, how each agent performs a local dynamic scheduling by selecting an adequate dispatching rule, and how agents can coordinate their actions to perform a global dynamic scheduling of the manufacturing system. Each agent can be implemented through object-oriented formalisms. The selection method is improved through the optimization of the numerical thresholds used in the detection of symptoms. This approach is compared with the use of SPT, SIX, MOD, CEXSPT and CR/SPT on a jobshop problem, already used in other research works. The results indicate significant improvements.     

复杂系统多智能体建模的博弈进化仿真

采用基于复杂系统多智能（Multi-Agent）体的整体建模仿真方法,利用Swarm仿真软件平台建立进化博弈仿真模型（EGM）,对该模型进行了描述和定义,运用EGM对各类对称博弈模型进行仿真运行,并对结果进行分析。仿真结果表明在不同类型的对称博弈中初始策略选择概率和收益矩阵对动态稳定策略的获得有不同的影响,在给定不同的收益矩阵和初始策略选择概率下可以获得不同的进化稳定策略。     

A multi-agent architecture for outsourcing SMEs manufacturing supply chain

In the present, global and competitive market customer's demands are very volatile. It is very difficult for small and medium size enterprises (SMEs) to satisfy their customer with quality product in reasonable price. Large firms are spending huge amount of their budget in generating technology development. To cope with this competitive market, usually, SMEs concentrate on their core expertise and outsource some non-core items or activities. The outsourcing decision (when, what, whom) is very crucial for small-scale industries. Realizing this scenario, in this article, an automated self-adaptive multi-agent system has been proposed. The proposed system will help SMEs to take an appropriate decision to mitigate the uncertainty in supply chain. The developed system exploits the “Outsourcing of operations” feature by its agents to conclude the manufacturing processes faster and reduce the idle time of certain machines with less human intervention. The communication protocol for agents has been described to give an insight of their communication. It was explained how various agents like outsourcing, material planning and supplier selection will come into action at different stages and take appropriate outsourcing decisions. Therefore, this multi-agent architecture will facilitate small scale manufacturing industries to execute their manufacturing processes and complex logistics issues efficiently. The execution of proposed architecture has been described in the simulated case study.     

新的RoboCup救援仿真分区消防策略

在RoboCup救援仿真的消防策略中,火势蔓延的控制对救援的效果有着重要的作用。大多数队伍采用基于单个建筑的各种指标的单目标选择法,该方法在着火建筑较多或者火势蔓延快时难以对火势进行有效控制。提出一种新的基于密度聚类的分区方法,根据火势蔓延速度将所有建筑进行聚类分析形成建筑簇并分开成为不同的区域,然后综合建筑的属性作为权值选择目标区域和灭火建筑,从而有效地控制火灾的蔓延甚至将火灾完全扑灭。最后通过仿真实验和比赛验证了该方法的有效性。     

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.     

A multi-agent architecture for dynamic scheduling of steel hot rolling

Steel production is a complex process and finding coherent and effective schedules for the wide variety of production steps, in a dynamic environment, is a challenging task. In this paper, we propose a multi-agent architecture for integrated dynamic scheduling of the hot strip mill (HSM) and the continuous caster. The scheduling systems of these processes have very different objectives and constraints, and operate in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. Each process is assigned to an agent which independently, seeks an optimal dynamic schedule at a local level taking into account local objectives, real-time information and information received from other agents. Each agent can react to real-time events in order to fix any problems that occur. We focus here, particularly, on the HSM agent which uses a tabu search heuristic to create good predictive–reactive schedules quickly. The other agents simulate the production of the coil orders and the real-time events, which occur during the scheduling process. When real-time events occur on the HSM, the HSM agent might decide whether to repair the current schedule or reschedule from scratch. To address this problem, a range of schedule repair and complete rescheduling strategies are investigated and their performance is assessed with respect to measures of utility, stability and robustness, using an experimental simulation framework.     

A multi-agent architecture for diagnosing simultaneous faults along water canals

Water is intensively used in mankind activities, in particular in agriculture. Water is commonly conveyed for agriculture purposes through water canal networks which are large-scale spatially distributed systems crossing extensive regions. In the presence of leaks, unauthorized water withdrawals, water depth sensor faults or gate faults, the quality of service can be severely compromised. A system able to diagnose which type of fault is present at a given time is of vital importance to access the current state of the water canal and proceed to restore its nominal condition. This paper proposes a multi-agent architecture to simultaneously detect, isolate and estimate lateral outflows (e.g., leaks or water withdrawals) and hardware faults (e.g., a gate obstruction or a downstream water depth sensor fault) in water canal networks. First, the main canal network is broken down into several subsystems composed of a single canal pool with the corresponding gate. Then, an agent is assigned to each subsystem aiming at its fault diagnosis. The approach is based on the generation and evaluation of residuals obtained from the comparison of model-based output signals with real data. Application to an experimental water canal bears out the proposed architecture as a valuable tool for monitoring and supervising general water canals.     

基于多Agent的策略驱动网络管理体系结构

通过对基于策略的管理技术和基于智能Agent分布式系统地分析,提出了一种策略驱动的基于多Agent的网络管理体系结构,利用了策略和Agent多种特性,适合实现面向服务和自治管理的分布式管理系统。     

RoboCup标准平台组中基于改进合同网协议的任务分配算法

针对RoboCup标准平台组SPL中多机器人之间的协同问题,提出了基于改进合同网协议的任务分配算法。首先对RoboCup多机器人系统建立层次结构分解模型和单体机器人行为任务树模型,并采用AHP层次分析法确定各个任务权重。其次,提出基于改进合同网协议的任务分配策略,相对于传统合同网协议,改进的合同网协议将标书公示机制引入任务分配模型;同时,提出了优先招标策略并对合同网协议流程和评价函数进行了改进和扩展。     

An integrated architecture for simulation

‘The explosion in computer performance allows average engineers to use simulation as part of the design process’ and enables them ‘to search all possible design alternatives, and find the one that best meets the overall design criteria’ by performing hundreds of simulations rather than just one or two. Yet, ‘the advanced analysts resist the effort, concerned that it would be hard to get the correct answers.’ An integrated architecture for simulation is proposed in this paper, which reduces the effort required for finding of the correct answers through integration of the simulation package with data-management (DM) software. The integrated architecture is based on three elements: input/output (I/O) handling, autonomous operation and control. I/O handling is provided by an add-on interface constructed in the DM tool, taking advantage of the fact that simulation software tools are increasingly able to exchange information with other software tools in an integrated way. All user interaction with the simulation can be done via this interface—input data entry, triggering the execution of simulation runs, and analyses of the results, which are automatically transferred by the simulation and recorded in the DM tool. Autonomous operation allows the execution of batch of simulation runs in the background leaving the user free to engage in other activities. Control, beyond providing the means for autonomous operation, enables the inclusion of simulation within larger context such as simulation–optimization schemes. Consequently, the integrated architecture allows simulation to be ‘routinely applied as a powerful, flexible and general purpose engine for optimization from the initial concept across the full product life cycle’.