一种无线传感器网络的多Agent系统模型

针对无线传感器网络缺乏普遍的理论模型,提出一种多Agent系统模型,包括形式化语言、模型、语义以及相应的公理和模型约束.该模型将无线传感器网络抽象为由具有特定信念、期望、意图和能力等认知成分的Agent组成的认知系统,所有这些认知成分构成多Agent系统认知模型.本文将为独立于内部结构和具体实现来理解、分析和预测无线传感器网络行为提供形式化的理论基础和分析工具.     

Reasoning about norms under uncertainty in dynamic environments

The behaviour of norm-autonomous agents is determined by their goals and the norms that are explicitly represented inside their minds. Thus, they require mechanisms for acquiring and accepting norms, determining when norms are relevant to their case, and making decisions about norm compliance. Up until now the existing proposals on norm-autonomous agents assume that agents interact within a deterministic environment that is certainly perceived. In practise, agents interact by means of sensors and actuators under uncertainty with non-deterministic and dynamic environments. Therefore, the existing proposals are unsuitable or, even, useless to be applied when agents have a physical presence in some real-world environment. In response to this problem we have developed the n-BDI architecture. In this paper, we propose a multi-context graded BDI architecture (called n-BDI) that models norm-autonomous agents able to deal with uncertainty in dynamic environments. The n-BDI architecture has been experimentally evaluated and the results are shown in this paper.     

A modelling language for cooperative plans in highly dynamic domains

Cooperative behaviour is one of the challenges most pronounced in the RoboCup Middle Size League. Especially the dynamic nature of the domain, which calls for swift adaptation by each robot and the team as a whole, is a distinctive property of the league. The ability to establish highly responsive teamwork while facing unreliable communication and sensory noise is a key to successful soccer teams. Moreover, modelling such responsive, cooperative behaviour is difficult. In this work, we specify a novel model for cooperative behaviour geared towards highly dynamic domains, focussing on the language syntax and semantics. In our approach, agents estimate each other’s decision and correct these estimations once they receive contradictory information. We provide a comprehensive approach for agent teamwork featuring intuitive modelling capabilities for multi-agent activities, abstractions over activities and agents, and a clear operational semantics. Moreover, we briefly present a graphical modeling tool for cooperative strategies, which is based directly on the theory laid out, together with a practical framework for executing said strategies. We show experimentally the responsiveness and coherence of the resulting team play.     

WDM环形自愈网

简要介绍了WDM环形自愈网的特点、故障的判定、隔离以及环形自愈网自激产生的条件及解决的办法     

Self-regulation through social institutions: A framework for the design of open agent-based electronic marketplaces

In this paper, we argue that allowing self-interested agents to activate social institutions during runtime can improve the robustness (i.e., stability, reliability, or scalability) of open multiagent systems (MAS). Referring to sociological theory, we consider institutions to be rules that need to be activated and adopted by the agent population during runtime and propose a framework for self-regulation of MAS for the domain of electronic marketplaces. The framework consists of three different institutional types that are defined by the mechanisms and instances that generate, change or safeguard them. We suggest that allowing autonomous agents both the reasoning about their compliance with a rule and the selection of an adequate institutional types helps to balance the trade-off between the autonomy of self-interested agents and the maintenance of social order (cf. Castelfranchi, 2000) in MAS, and to ensure almost the same qualities as in closed environments. A preliminary report of the evaluation of the prototype by empirical simulations is given. Christian S. Hahn studied computer science and economics at Saarland University and received his diploma in 2004. Currently, he works in a project of the priority program ‘Socionics’ funded by the German Research Foundation at the German Research Center for Artificial Intelligence (DFKI). Bettina Fley studied sociology, economics, law, and social and economic history at the University of Hamburg and received her diploma in 2002. She currently works in a project in the priority program ‘Socionics’, which is funded by the German Research Foundation (DFG), at the Department of Technology Assessment at the Hamburg University of Technology. Michael Florian, received his master in sociology at the University of Münster, where he also finished his doctoral degree in 1993. Since 1995, he holds a position as a senior researcher (‘Oberingenieur’) at the Department of Technology Assessment at the Hamburg University of Technology and heads the sociological part of a project in the priority program ‘Socionics’ funded by the German Research Foundation (DFG).     

MPLS网络中的OAM

网络操作、管理与维护（OAM）在公用网中非常重要,它能够提高网络可靠性,简化操作,降低网络运行成本。本讨论了在MPLS（多协议标记交换）网络中通过OAM数据包来实现OAM功能的方法,并在分析网络管理需求的前提下,提出了几种在MPLS层实现OAM功能的方案,展望了MPLS OAM标准的发展方向。     

Improving the adaptability in automated vessel scheduling in container ports using intelligent software agents

Faster turnaround time of vessels and high berth productivity are paramount factors in container terminals for assuring competitive advantage in the shipping industry. An autonomous decision-making capability in the terminal is vital in achieving the required productivity. Vessel scheduling/berthing system in a container terminal is regarded as a very complex dynamic application in today’s business world. The Artificial Intelligence (AI) community has been researching in the field of intelligent (or rational) agents for more than a decade and implementations are found in many commercial applications. The Beliefs, Desires and Intention (BDI) agent architecture is probably the most mature model for many industrial applications in today’s context. However, it is not the best agent model for complex applications that must learn and adapt their behaviours in making rational decisions. We propose a new hybrid BDI framework with an intelligent module to overcome the limitations in the generic BDI model. Learning and the adaptability of the environments are assured with the introduction of the Knowledge Acquisition Module (KAM) in the generic BDI architecture in our proposed framework. The dynamic selection of the intention structures has been improved with a trained neural network. The knowledge required to handle vagueness or uncertainty in the environment has been modelled with an Adaptive Neuro Fuzzy Inference System (ANFIS) in berths. Finally, the benefits and the usability of hybrid BDI model for a vessel berthing application is discussed with experiential results.     

BSS:基于BDI对手模型的MANET自组织安全分簇

MANET是军用、民用领域都具有很大潜力的一种新型无线网络,大规模MANET的组建必须采用以分簇实现的层次结构。MANET的现有分簇算法一般较少考虑安全性。文中基于MANET的自组织特性和移动节点的Agent特性,采用网络自组织思想及设计规范和理性Agent设计模型,建立了移动节点的BDI对手模型,提出了包含博弈分析的The-Second和Switch-Head算法,并在此基础上建立了一个新的安全分簇算法—BSS。分析表明,此算法具有较好的安全性与较高的性能。     

基于MPC8241管理板的设计与实现

CPU管理板在交换机中起管理作用,以便网管人员可以对交换机进行灵活的实时监控和全局管理.该文介绍了一种基于摩托罗拉公司MPC8241的CPU管理板.首先介绍了基于该CPU管理板的硬件结构和特点,以及软件所采用的操作系统和完整的开发工具.接着详细给出了结合以上的硬件和软件来开发管理板的具体的实现步骤.为广大工程技术人员提供参考.