Intelligent policy recommendations on enterprise resource planning by the use of agent technology and data mining techniques

Enterprise Resource Planning systems tend to deploy Supply Chain Management and/or Customer Relationship Management techniques, in order to successfully fuse information to customers, suppliers, manufacturers and warehouses, and therefore minimize system-wide costs while satisfying service level requirements. Although efficient, these systems are neither versatile nor adaptive, since newly discovered customer trends cannot be easily integrated with existing knowledge. Advancing on the way the above mentioned techniques apply on ERP systems, we have developed a multi-agent system that introduces adaptive intelligence as a powerful add-on for ERP software customization. The system can be thought of as a recommendation engine, which takes advantage of knowledge gained through the use of data mining techniques, and incorporates it into the resulting company selling policy. The intelligent agents of the system can be periodically retrained as new information is added to the ERP. In this paper, we present the architecture and development details of the system, and demonstrate its application on a real test case.     

基于Agent的航空安全管理智能决策支持系统

基于基元事件分析法，给出了一个Internet上用多Agent实现的航空公司安全管理智能决策支持系统AAIDSS的设计与实现方法，该系统在决策支持系统3库结构的基础上，采用了多智能体技术。提出了由OLTP处理、基础结构部分、Agent组织共同组建智能决策支持系统的框架模型，给出了事故分析Agent、界面Agent的核心技术。AAIDSS的设计和实现方法，对于构建基于Intranet的中小型智能决策支持系统具有普遍的参考价值。     

基于优先数的智能生产调度系统

生产调度是企业生产中的关键环节,也是实施CIMS的重点。该文介绍了一种基于优先数的动态、多目标优化生产调度方法,并构造了一个基于优先数的智能生产调度系统。系统通过Agent对生产调度问题中的各个目标优化,给出不同目标的指标值,同时给出企业在不同时候对不同目标的偏好值,计算各个生产任务的优先数,根据任务的优先数安排生产。     

多Agent系统模型及其应用

文章提出了基于访问、感知和知识的多Agent系统模型。从特定环境中的Agents为完成一定的任务所应具备的能力的角度出发,引入了环境状态划分函数、感知函数以及状态转移函数等来对Agents和环境进行研究并建立系统模型。该模型是合理的、自然的。同时,它还区分外部环境与Agents环境中可访问的信息,Agents感知到的信息以及Agents知道的信息,并研究了系统的运行过程。接下来,通过具体的实例来说明模型的具体应用。最后进行总结并讨论了进一步的研究工作。     

DPMAS:一种多主体系统设计方法

提出一种多主体系统设计方法DPMAS。首先,该方法以对象作为主体实现的基础,以UML作为基本的建模语言,保证了与面向对象方法的延续性。同时,该方法提供了新的图来表示多主体系统中的知识模型和主体间交互模型,并对UML符号进行了一些改进以表示主体特有的概念。     

一种不完全信息下的多智能体协作机制

在分布式多智能体系统中，由于agen嗵常具有不完全信息，因此大大影响了系统的协作效果。该文采用博弈论和决策理论相结合的方法，将不完全信息下的agcnt协作转换成完全信息下agent协作问题来求解，提出了一种不完全信息下的agent协作机制。     

Multi-agent segmentation of IVUS images

A novel multi-agent image interpretation system has been developed which is markedly different from previous approaches in especially its elaborate high-level knowledge-based control over low-level image segmentation algorithms. Agents dynamically adapt segmentation algorithms based on knowledge about global constraints, contextual knowledge, local image information and personal beliefs. Generally agent control allows the underlying segmentation algorithms to be simpler and be applied to a wider range of problems with a higher reliability.The agent knowledge model is general and modular to support easy construction and addition of agents to any image processing task. Each agent in the system is further responsible for one type of high-level object and cooperates with other agents to come to a consistent overall image interpretation. Cooperation involves communicating hypotheses and resolving conflicts between the interpretations of individual agents.The system has been applied to IntraVascular UltraSound (IVUS) images which are segmented by five agents, specialized in lumen, vessel, calcified-plaque, shadow and sidebranch detection. IVUS image sequences from 7 patients were processed and vessel and lumen contours were detected fully automatically. These were compared with expert-corrected semiautomatically detected contours. Results show good correlations between agents and expert with r=0.84 for the lumen and r=0.92 for the vessel cross-sectional areas, respectively.     

Distributed intelligence for multi-camera visual surveillance

Latest advances in hardware technology and state of the art of computer vision and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. The paper proposes a multi-agent architecture for the understanding of scene dynamics merging the information streamed by multiple cameras. A typical application would be the monitoring of a secure site, or any visual surveillance application deploying a network of cameras. Modular software (the agents) within such architecture controls the different components of the system and incrementally builds a model of the scene by merging the information gathered over extended periods of time. The role of distributed artificial intelligence composed of separate and autonomous modules is justified by the need for scalable designs capable of co-operating to infer an optimal interpretation of the scene. Decentralizing intelligence means creating more robust and reliable sources of interpretation, but also allows easy maintenance and updating of the system. Results are presented to support the choice of a distributed architecture, and to prove that scene interpretation can be incrementally and efficiently built by modular software.     

RESEARCH ON CAPP／SCHEDULING INTEGRATION MULTI-AGENT SYSTEM MODEL AND IMPLEMENTATION

A design methodology fOr multi-agent systems is proposed. The systemic framework ofCAPP and scheduling integrated multi-agent system according to design methodology is researched.Agent model, composition model and cooperation model are discussed respectively in the multi-agentsystem.Static composition model and dynamic running model of CAPP and scheduling integrated     

Leader-following consensus for a class of second-order nonlinear multi-agent systems

This paper deals with the leader-following consensus problem for a class of multi-agent systems with nonlinear dynamics and directed communication topology. The control input of the leader agent is assumed to be unknown to all follower agents. A distributed adaptive nonlinear control law is constructed using the relative state information between neighboring agents, which achieves leader-following consensus for any directed communication graph that contains a spanning tree with the root node being the leader agent. Compared with previous results, the nonlinear functions are not required to satisfy the globally Lipschitz or Lipschitz-like condition and the adaptive consensus protocol is in a distributed fashion. A numerical example is given to verify our proposed protocol.