Multiagent System for Condition-Monitoring Applications

Condition monitoring, within the power industry, is essential to ensure continuous operation and health of electrical plans. This is a complex activity that requires the combination of different artificial intelligence techniques. This article describes a multiagent framework to support such a condition-monitoring approach. The resulting condition monitoring multiagent system (COMMAS) was applied to two different case studies, to monitor the start-up sequences of industrial gas turbines and identification of partial discharge signal defects in gas insulated substations.     

QOCA: A Constraint Solving Toolkit for Interactive Graphical Applications

We describe an object-oriented constraint solving toolkit, QOCA, designed for interactive graphical applications. It has a simple yet powerful interface based on the metric space model for constraint manipulation. In this model interaction with the constraint solver can occur in three ways: a constraint may be added, a constraint may be deleted, or values for designated edit variables may be suggested. Currently, QOCA supports linear arithmetic constraints and two different metrics: the square of the Euclidean distance and Manhattan distance. It provides three solvers, all of which rely on keeping the constraints in solved form and relies on novel algorithms for efficient resolving of constraints during direct manipulation. We provide a thorough evaluation of QOCA, both of the interface design and the speed of constraint solving.     

RFID Applications: Interfacing with Readers

Improving efficiency is a major driver for increasing workflow automation and data integration, whether in software development or in application domains such as enterprise computing. Recently, RFID has been boosting workflow efficiency across production and supply networks. This physical identification technology relies on radio transmitters and receivers embedded in products of all types to itt >re and remotely retrieve data. It illustrates how the traditionally separate worlds of embedded and IT software are merging, and it demands skills in both worlds. Christian Floerkemeier and Flgar Fleisch describe the software issues in deploring RFID.     

A Framework for Coordinated Control of Multiagent Systems and Its Applications

In this paper, a framework is proposed for the distributed control and coordination of multiagent systems (MASs). In the proposed framework, the control of MASs is regarded as achieving decentralized control and coordination of agents. Each agent is modeled as a coordinated hybrid agent, which is composed of an intelligent coordination layer and a hybrid control layer. The intelligent coordination layer takes the coordination input, plant input, and workspace input. In the proposed framework, we describe the coordination mechanism in a domain-independent way, i.e., as simple abstract primitives in a coordination rule base for certain dependence relationships between the activities of different agents. The intelligent coordination layer deals with the planning, coordination, decision making, and computation of the agent. The hybrid control layer of the proposed framework takes the output of the intelligent coordination layer and generates discrete and continuous control signals to control the overall process. To verify the feasibility of the proposed framework, experiments for both heterogeneous and homogeneous MASs are implemented. The proposed framework is applied to a multicrane system, a multiple robot system, and a MAS consisting of an overhead crane, a mobile robot, and a robot manipulator. It is demonstrated that the proposed framework can model the three MASs. The agents in these systems are able to cooperate and coordinate to achieve a global goal. In addition, the stability of systems modeled using the proposed framework is also analyzed.     

PIBG Toolkit:一个笔式界面工具箱的分析与设计

PIBG Toolkit是一个基于PIBG交互范式构造而成的笔式应用开发平台．PIBG Toolkit中包含了纸、框等多种交互组件,定义了纸、框和内容三个层次之间的静态结构和动态机制．开发者开发笔式交互系统时,可以用PIBG Toolkit来建立整体的软件框架和交互机制,并有选择地在系统中添加Toolkit。中所提供的交互组件,这样,开发者的精力将会集中在应用领域的内容上。目前,基于该平台已经开发出多个具有很好应用前景的笔式应用系统。     

Metis – An Object-Oriented Toolkit for Constructing Virtual Reality Applications

Virtual reality systems provide realistic look and feel by seamlessly integrating three-dimensional input and output devices. One software architecture approach to constructing such systems is to distribute the application between a computation-intensive simulator back-end and a graphics-intensive viewer front-end which implements user interaction. In this paper we discuss Metis, a toolkit we have been developing based on such a software architecture, which can be used for building interactive immersive virtual reality systems with computationally intensive components. The Metis toolkit defines an application programming interface on the simulator side, which communicates via a network with a standalone viewer program that handles all immersive display and interactivity. Network bandwidth and interaction latency are minimized, by use of a constraint network on the viewer side that declaratively defines much of dynamic and interactive behavior of the application.     

WebCom:一个基于Web技术的计算网格入口工具包

以西安交通大学校园网格计算环境建设为背景,分析了网格入口的概念和基本技术,设计并实现了一个基于Web技术的计算网格入口工具包——WebCom,它给计算网格系统用户提供了访问网格系统资源的良好交互界面、一致的使用模式和“傻瓜式”的使用方法,从而解决了网格系统使用复杂的问题。WebCom在设计和实现中充分考虑了系统的安全性、透明性、好用性、完备性等特点,并进行了测试,给出了测试结果和评价,为今后同类系统的设计、开发和实现提供了一个详细的参考模型。     

JAAFAAR: A Web-Based Multi-Agent Toolkit for Collective Research

This paper introduces a generic and opened multi-agent platform that provides a powerful scientific equipment for collective research on self-organized systems. A general thought on the mutation of object model towards the agent model is presented. The paper details the construction of the platform upon generic models of environment and agent. Then we present the extension of the toolkit to web-based technologies, and its suitability for collective research and remote works.     

数据挖掘工具集TH-Miner

TH-Miner是以JaVa实现的跨平台数据挖掘可视化系统。在TH-Miner中实现了多种经典的数据挖掘算法,并构造了几种新的改进算法。TH-Miner包括可视化聚类挖掘工具、分类算法工具、序列模式挖掘算法工具以及文本分类工具。     

A Hybrid Intelligent Multiagent System for E-Business

The paper describes a new multiagent system with enhanced capabilities obtained through a hybrid of intelligent techniques. The processing in the model is handled by two types of agents: distributed agents and a central administrator agent. Localized processing at the individual agents is carried out using mathematical techniques and genetic algorithms. The central administrator agent dynamically obtains information about the problem domain from the Internet and maintains a knowledge pool using a clustering technique called the growing self-organizing map (GSOM). Distributed agents communicate with the central administrator agent if they need further knowledge about the problem domain to provide solutions to user-defined tasks. The approach integrates traditional mathematical, data mining, and evolutionary techniques with a multiagent system. The proposed system is implemented as a travel optimizer application for the e-tourism domain. Finally, the possibilities of integrating the proposed technique with currently available e-tourism applications to provide the customer with enhanced solutions are identified.     

A Multiagent Platform for Ubiquitous Service Provision

The Virtual Home Environment is very important in contemporary mobile telecommunications infrastructure as it caters for the ubiquitous provision of services irrespective of network, location and user device. The universality of systems like Universal Mobile Telecommunications System and wi-fi increases the need for the rapid introduction of efficient VHE schemes. In this paper, we study the adoption of Mobile Agents for handling the VHE functionality. Mobile agents are nicely harmonized with the broader idea of VHE as they allow the autonomous execution of tasks by components that roam from node to node and network to network. We present the detailed modeling of a VHE provisioning architecture and investigate its suitability for different use cases and technical options (e.g., end user devices). The adoption of mobile agents for the ubiquitous provision of telecommunication services is quite promising in terms of efficiency. Through a series of experiments we quantify the performance benefits stemming from the adoption of mobile agents in contrast to conventional service provisioning schemes.     

Advanced Adaptive Sonar for Mapping Applications

An advanced adaptive sonar module is described, capable of being configured to different circumstances and distances according to reflectors found in the environment. Thanks to the sensory distribution, it is possible to identify three basic types of reflector (planes, edges and corners). Furthermore, a heuristic map of the environment is built. The proposed methods have been computationally optimized, and implemented in a real-time system based on a Field-Programmable Gate Array (FPGA) and a Digital Signal Processor (DSP). Results have been obtained in the detection, classification and mapping of obstacles; and finally testing has been carried out on a commercial vehicle.     

A Multiagent Evolutionary Algorithm for Combinatorial Optimization Problems

Based on our previous works, multiagent systems and evolutionary algorithms (EAs) are integrated to form a new algorithm for combinatorial optimization problems (CmOPs), namely, MultiAgent EA for CmOPs (MAEA-CmOPs). In MAEA-CmOPs, all agents live in a latticelike environment, with each agent fixed on a lattice point. To increase energies, all agents compete with their neighbors, and they can also increase their own energies by making use of domain knowledge. Theoretical analyses show that MAEA-CmOPs converge to global optimum solutions. Since deceptive problems are the most difficult CmOPs for EAs, in the experiments, various deceptive problems with strong linkage, weak linkage, and overlapping linkage, and more difficult ones, namely, hierarchical problems with treelike structures, are used to validate the performance of MAEA-CmOPs. The results show that MAEA-CmOP outperforms the other algorithms and has a fast convergence rate. MAEA-CmOP is also used to solve large-scale deceptive and hierarchical problems with thousands of dimensions, and the experimental results show that MAEA-CmOP obtains a good performance and has a low computational cost, which the time complexity increases in a polynomial basis with the problem size.      

A Reluctance-Based Cost Distribution Strategy for Multiagent Planning

In this paper we present CODMAPS, a COst Distribution Method for Agent Planning Systems. The strategy is based on individual distribution of cost and competitive behavior.Our model emulates how human agents work in expert groups. They all share a common objective, however, they also have individual interests and try to steer the planning process towards their own goals. Two opposing trends coexist within the set: global co-operation and individual utility maximization. External evaluation must guarantee the validity of the final plan at global level, but a negotiation and cost distribution strategy must ensure that cost is adequately shared throughout the agent set. We introduce the concept of reluctance as a regulation mechanism to facilitate it. A statistical model allows agents to adapt their attitude towards negotiation depending on their negotiation state vector , which encompasses all history of previous negotiations by the agent.Previous research into this problem had taken the rational approach. A group of agents choose the best alternative given the current possibilities. This not only forces the agents to exchange and understand other agents' proposals (which is computationally expensive), but also neglects the past negotiation history of each individual agent.Our approach facilitates distribution of cost across the agent set given the agents' past history and the importance of their constraints. The more taxed an agent becomes the more reluctant it will be to relax, thus pushing other agents less taxed to accept to compromise. It does not need explicit constraint information exchange, thus simplifying the negotiation process.     

Proplant: Multiagent system for production planning

The so-called ''tribase'' acquaintance model of the agent's behavior is presented in this paper. This represents an extension of the twin-base model (Cao et al., 1997). Based on practical experience, the new model tries to cope with parallel processing, precedence constraints, and sparse resources. The idea of substituting the interagent negotiation processes by the periodical internal planning activity of the agents is stressed. A multiagent system, ProPlanT, as an application of the tribase model for the project-oriented production planning developed for TESLA TV company is described in detail. Three types of agents production planning agent (PPA), production management agent (PMA), and production agent (PA) are distinguished. The corresponding tribase models and potential role of metaagents are discussed.