Agent通信及多Agent系统(MAS协作机制的研究)

Agent及多Agent系统(Multi—Agent system,MAS)已被视为一种新的软件设计风格。本文在介绍了Agent的概念与BDI模型的基础上,分析了Agent的通信类型、通信规划以及多Agent系统(MAS)的基本模型与体系结构,同时对MAS的协作、协商、协调机制进行了深入研究,提出了远程通信和移动Agent通信概念。     

建立DAI系统的组织模型

在ＤＡＩ系统中组织是多主体间实现有效协同的基本要素之一,针对处理大粒度结点集成的ＤＡＩ系统提出“系统组织模型”的概念,系统组织模型定义ＤＡＩ系统的组织结构,形式和组织原则,这些定义形成关于一个法律和规范为前提。建立系统组织 目的在于明确而完整地表示系统组织的结构和整体性质,以引导各主体的设计,实现和协作求解,增强系统的全局连贯性。     

Intelligent multiagent application system in an AI system

This article presents an intelligent multiagent application system in AI. The research trend into multiagents is changing from a centralized computing environment to a distributed computing environment. Also, the research into multiagents can be changed to a mobile environment. Initially, the study of multiagents is from research into human modeling. Therefore, we fi rst present a brief concept of a mobile multiagent, and then we present some application areas for mobile multiagents, especially in elearning, bioinformatics, control, and information retrieval, etc. Finally, we present the research theme of multiagents in AI. This work was presented in part at the 12th International Symposium on Articial Life and Robotics, Oita, January 25–27, 2007     

An appraisal and design of a multi-agent system based cooperative wireless intrusion detection computational intelligence technique

The deployment of wireless sensor networks and mobile ad-hoc networks in applications such as emergency services, warfare and health monitoring poses the threat of various cyber hazards, intrusions and attacks as a consequence of these networks’ openness. Among the most significant research difficulties in such networks safety is intrusion detection, whose target is to distinguish between misuse and abnormal behavior so as to ensure secure, reliable network operations and services. Intrusion detection is best delivered by multi-agent system technologies and advanced computing techniques. To date, diverse soft computing and machine learning techniques in terms of computational intelligence have been utilized to create Intrusion Detection and Prevention Systems (IDPS), yet the literature does not report any state-of-the-art reviews investigating the performance and consequences of such techniques solving wireless environment intrusion recognition issues as they gain entry into cloud computing. The principal contribution of this paper is a review and categorization of existing IDPS schemes in terms of traditional artificial computational intelligence with a multi-agent support. The significance of the techniques and methodologies and their performance and limitations are additionally analyzed in this study, and the limitations are addressed as challenges to obtain a set of requirements for IDPS in establishing a collaborative-based wireless IDPS (Co-WIDPS) architectural design. It amalgamates a fuzzy reinforcement learning knowledge management by creating a far superior technological platform that is far more accurate in detecting attacks. In conclusion, we elaborate on several key future research topics with the potential to accelerate the progress and deployment of computational intelligence based Co-WIDPSs.     

Integrating multi-agent negotiation to resolve constraints in fulfilling supply chain orders

As the order fulfillment process (OFP) in supply chains shifts to outsourcing paradigm, the OFP performance relies on the coordination among supply chain partners to reach executable and effective plans. The coordination of OFP among supply chain partners can be viewed as a distributed constraint satisfaction problem (DCSP). This study adds the multi-agent negotiation mechanism to enhance the existing methods to solve the DCSP, and then evaluates the integrated system’s performance through experimentation on the OFP in the context of the metal industry. The experimental results show that the integrated system outperforms the existing distributed constraint satisfaction algorithms in various demand patterns.     

基于MAS的城市应急中心系统设计

面向Agent编程（Agent—Oriented Programming,AOP）是一种重要的软件设计思想。基于Agent技术的软件工程方法构建的多Agent系统（Multiagent System,MAS）具有模块化程度较高、运行速度较快、鲁棒性和扩充性较强等优点,因此,MAS构建的CSCW平台逐渐应用于很多领域。另一方面,现有的城市应急中心（110／122／119）系统都是独立封闭的系统、各中心之间缺乏协调能力、只能机械地执行规定的动作,不能满足社会联动多态性服务的要求,该文在分析现状和缺陷的基础上,将AOP软件设计思想引入到了城市应急中心系统设计（乃至一般的应急中心系统设计）中,提出了一种基于MAS的城市应急中心系统框架模型,并详细阐述了系统设计中所涉及的关键技术。     

Evidential calibration process of multi-agent based system: An application to forensic entomology

Forensic entomology consists, during a criminal investigation, in studying the insects found on a cadaver to estimate the time of death. This is the only technique that can be used for a large post-mortem interval. But, because of the important system complexity, the result given by the expert are imperfect. In this paper, a decision support system (DSS) has been developed to take into account all the ecosystemic parameters and a significant quantity of biological models. The proposed DSS is based on the belief function theory to validate and calibrate agent based simulations. First results of this architecture are presented within the framework of a real forensic examination.     

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.     

An abstract knowledge based approach to diagnosis and recovery of plan failure in multi-agent systems

Open multi-agent systems (MAS) are decentralised and distributed systems that consist of a large number of loosely coupled autonomous agents. In the absence of centralised control they tend to be difficult to manage, especially in an open environment, which is dynamic, complex, distributed and unpredictable. This dynamism and uncertainty in an open environment gives rise to unexpected plan failures. In this paper we present an abstract knowledge based approach for the diagnosis and recovery of plan action failures. Our approach associates a sentinel agent with each problem solving agent in order to monitor the problem solving agent’s interactions. The proposed approach also requires the problem solving agents to be able to report on the status of a plan’s actions.Once an exception is detected the sentinel agents start an investigation of the suspected agents. The sentinel agents collect information about the status of failed plan abstract actions and knowledge about agents’ mental attitudes regarding any failed plan. The sentinel agent then uses this abstract knowledge and the agents’ mental attitudes, to diagnose the underlying cause of the plan failure. The sentinel agent may ask the problem solving agent to retry their failed plan based on the diagnostic result.     

Dynamic workforce allocation in a constrained flow shop with multi-agent system

The present work addresses the problem of real time workforce scheduling in assembly lines where the number of operators is less to the number of workstations.The problem is faced developing a two-steps procedure made of (i) a centralized scheduling based on a constraint optimization problem (COP) for initial operator scheduling, and (ii) a decentralized algorithm performed by a multiagent system (MAS) to manage workers in case of unforeseen events.In the proposed MAS architecture, Agents represent the operators trying to find local assignments for themselves. The system is validated with a simulation model and implemented with a hardware infrastructure in a real assembly line of electromechanical components. The main original contribution of the paper consists in proving – by means of both validation through a simulation model and test in a real assembly line of electromechanical components – that (1) multi-agent systems could be successfully adopted to solve a workforce scheduling problem, and (2) a combined approach consisting of centralized + distributed approach would provide better results compared with the application of one of the two approaches alone.     

A novel multi-agent approach to identify faults in line connected three-phase induction motors

Three-phase induction motors (TIMs) are the key elements of electromechanical energy conversion in a variety of productive sectors. Identifying a defect in a running motor, before a failure occurs, can provide greater security in the decision-making processes for machine maintenance, reduced costs and increased machine operation availability. This paper proposes a new approach for identifying faults and improving performance in three-phase induction motors by means of a multi-agent system (MAS) with distinct behavior classifiers. The faults observed are related to faulty bearings, breakages in squirrel-cage rotor bars, and short-circuits between the coils of the stator winding. By analyzing the amplitudes of the current signals in the time domain, experimental results are obtained through the different methods of pattern classification under various sinusoidal power and mechanical load conditions for TIMs. The use of an MAS to classify induction motor faults allows the agents to work in conjunction in order to perform a specific set of tasks and achieve the goals. This technique proved its effectiveness in the evaluated situations with 1 and 2 hp motors, providing an alternative tool to traditional methods to identify bearing faults, broken rotor bars and stator short-circuit faults in TIMs.     

An application of artificial intelligence to the choreography of dance

This paper describes an experimental computer program that applies the techniques of artificial intelligence to the creation of dance. Specifically, a user expresses a set of dance rules (in a special English-like rule language) which describes some of the dynamic aspects of a dance. These rules are applied nondeterministically by a rule driver program. The rules themselves are similar to those that form the knowledge base of expert systems. The rule driver embodies a heuristic algorithm of the type found in many artificial intelligence programs.James H. Bradford is an Associate Professor of Computer Science at Brock University. He is an active researcher in the area of Human/Computer Interaction with particular interests in the analysis of speech and the representation of dance.Paulette Côté-Laurence is an Associate Professor of Physical Education at Brock University. Her research interests are in the areas of motor control and the acquisition of dance skills, psychology of rhythm, and dance technology.     

Cascade explicit tube model predictive controller: application for a multi-robot system

In recent years, there has been a growing demand for more efficient and robust control strategies in cooperative multi-robot systems. This paper introduces the cascade explicit tube model predictive controller (CET-MPC), a control architecture designed specifically for distributed aerial robot systems. By integrating an explicit model predictive controller (MPC) with a tube MPC, our approach significantly reduces online computational demands while enhancing robustness against disturbances such as wind and measurement noise, as well as uncertainties in inertia parameters. Further, we incorporate a cascade controller to minimize steady-state errors and improve system performance dynamically. The results of this assessment provide valuable insights into the effectiveness and reliability of the CET-MPC approach under realistic operating conditions. The simulation results of flight scenarios for multi-agent quadrotors demonstrate the controller’s stability and accurate tracking of the desired path. By addressing the complexities of quadrotors’ six degrees of freedom, this controller serves as a versatile solution applicable to a wide range of multi-robot systems with varying degrees of freedom, demonstrating its adaptability and scalability beyond the quadrotor domain.     

基于Agent的NMD分布仿真系统建模分析

在未来的高技术局部战争中,导弹攻防对抗将成为一个重要的内容。建立实用的国家导弹防御(NMD)分布式仿真系统用于攻防对抗仿真,并结合相应的实验和分析手段来支持未来新型号战略导弹突防的总体设计,是导弹武器发展亟待解决的重大问题。该文从NMD系统的组成、NMD攻防对抗的一般过程及特点的分析出发,重点阐述了基于Agent的NMD系统的建模仿真过程、层次结构、接口关系、个体Agent的模型结构及系统实现的关键技术等,在一个新的视点上来研究了 NMD攻防对抗分布式仿真。     

基于地理信息系统的情报应用系统的设计与实现

情报数据具有数据来源广泛、数据格式种类多、数据量大等特点.将地理信息系统技术应用于构建情报应用系统可以解决情报数据的一体化存储与管理以及矢量、栅格、多媒体等情报数据的显示、处理、分析等诸多问题.重点介绍了基于GIS的情报应用系统的体系结构、情报数据模型和系统功能,并在此基础上总结出系统的特点.     

An LMI-based approach to critical control system design for rate-limited exogenous inputs

This paper considers a linear matrix inequality approach to the design of critical control systems for rate-limited exogenous inputs. The sufficient condition for ensuring the critical requirement is derived from the exponential convergence condition of the unit step response. By changing the variables, it is transformed into the set of BMI and LMI conditions. The problem amounts to a convex feasibility problem with a line search. The obtained controller has the same order as a plant. To show the validity of the proposed method, a numerical example of multi-conditioned critical control system design is presented.     

An adaptive algorithm based on the immune system and its application to adaptive noise neutralization

We propose an adaptive algorithm based on some features of the immune system (a selection-based mechanism compatible with Edelman’s selectionist principle, self/nonself reference, and negative/positive selection). The algorithm proceeds in three steps: diversity generation, establishment of self-tolerance, and memorizing nonself. This algorithm may typically be used to model the system of distributed agents where the system (the self) as well as the environment (the nonself) are unknown or cannot be modeled. An agent-based architecture based on the local memory hypothesis and a network-based architecture based on the network hypothesis are discussed. The agent-based architecture is elaborated with applications to an adaptive system where knowledge about the environment is not available. An adaptive noise neutralizer is formalized and simulated for a simple plant. Some part of this work has been presented at ICEC 1996, IROS 1996, and AROB 1999.