Intelligent interaction design: the role of human-computer interaction research in the design of intelligent systems

As more intelligent systems are introduced into the marketplace, it is becoming increasingly urgent to consider usability for such systems. Historically, the two fields of artificial intelligence (AI) and human- computer interaction (HCI) have had little in common. In this paper, we consider how established HCI techniques can usefully be applied to the design and evaluation of intelligent systems, and where there is an urgent need for new approaches. Some techniques - notably those for requirements acquisition and empirical evaluation - can usefully be adopted, and indeed are, within many projects. However, many of the tools and techniques developed within HCI to support design and theory-based evaluation cannot be applied in their present forms to intelligent systems because they are based on inappropriate assumptions; there is consequently a need for new approaches. Conversely, there are approaches that have been developed within AI - e.g. in research on dialogue and on ontologies - that could usefully be adapted and encapsulated to respond to this need. These should form the core of a future research agenda for intelligent interaction design.     

A metagenetic algorithm for information filtering and collection from the World Wide Web

This paper describes the implementation of evolutionary techniques for information filtering and collection from the World Wide Web. We consider the problem of building intelligent agents to facilitate a person's search for information on the Web. An intelligent agent has been developed that uses a metagenetic algorithm in order to collect and recommend Web pages that will be interesting to the user. The user's feedback on the agent's recommendations drives the learning process to adapt the user's profile with his/her interests. The software agent utilizes the metagenetic algorithm to explore the search space of user interests. Experimental results are presented in order to demonstrate the suitability of the metagenetic algorithm's approach on the Web.     

Exploring the Interaction between Java's Implicitly Thrown Exceptions and Instruction Scheduling

The frequent occurrence of implicitly thrown exceptions poses one of the challenges present in a Java compiler. Not only do these implicitly thrown exceptions directly affect the performance by requiring explicit checks, they also indirectly impact the performance by restricting code movement in order to satisfy the precise exception model in Java. In particular, instruction scheduling is one transformation that is restricted by implicitly thrown exceptions due to the heavy reliance on reordering instructions to exploit maximum hardware performance. The goal of this study is two-fold: first, investigate the degree to which implicitly thrown exceptions in Java hinder instruction scheduling, and second, find new techniques for allowing more efficient execution of Java programs containing implicitly thrown exceptions. Experimental results show that with aggressive scheduling techniques, such as superblock scheduling, the negative performance impact can be greatly reduced.     

A Reusable Multi-Agent Architecture for Active Intelligent Websites

In this paper a reusable multi-agent architecture for intelligent Websites is presented and illustrated for an electronic department store. The architecture has been designed and implemented using the compositional design method for multi-agent systems DESIRE. The agents within this architecture are based on a generic information broker agent model. It is shown how the architecture can be exploited to design an intelligent Website for insurance, developed in co-operation with the software company Ordina Utopics and an insurance company.     

Locally perceiving hard global constraints in multi-agent scheduling

We propose how to model enterprise facilities (like factories, warehouses, etc.) in a multi-product production/distribution network, capacity management at those facilities, and scheduling agents which act as enterprise managers, taking decisions that affect the available capacity. A coordination mechanism through which scheduling agents can locally perceive hard global temporal constraints is also proposed.     

A multi-agent intelligent system for efficient ERP maintenance

The Enterprise Resource Planning (ERP) system is an enterprise-wide integrated software package designed to uphold the highest quality standards of business process. However, for the time being, when the business condition has been changed, the system may not guarantee that the process embedded in ERP is still best. Moreover, since the ERP system is very complex, maintaining the system by trial and error is very costly. Hence, this paper aims to construct a support system that adjusts ERP system to environmental changes. To do so, we adopt multi-agent intelligent technology that enables autonomous cooperation with one another to monitor ERP databases and to find any exceptional changes and then analyze how the changes will affect ERP performance. Moreover, Petri net is applied to manage the complexity and dynamics of agents’ behavior. To show the feasibility of the idea, a prototype agent system, ERP/PN, is proposed and an experiment is conducted.     

超立方体网络中任务调度的一个新近似算法

本文研究超立方体中的多处理器任务调度问题,我们研究LDLPT算法并指出为什么这种算法对一些实例具有最差的逼近度,然后提出一种类似装箱算法的新算法-BPA算法,证明该算法和LDLPT算法在相互最差逼近度中具有互补性质,最后,组合这两种算法的基本方法提出了一种求解问题的新算法-CBPA算法,并证明新算法具有比LDLPT算法更好的逼近度。     

一种基于多代理技术实现的虚拟企业中的敏捷调度

提出了一种用多代理技术和基于协商的策略解决虚拟企业调度冲突的方法。首先介绍了虚拟企业中敏捷调度的特性及调度冲突的产生,分类及解决方法,并描述了调度、计划、协商、监督执行之间的互操作,通过代理的智能,自治等特性可以较好地实现调度的敏捷性,最后给出了在一个面向虚拟企业的信息集成系统ViaSopc中基于多代理技术实现的基于协商的敏捷调度模型。     

最短响应时间优先请求分配算法的研究

分析了在分布式高性能防火墙中两种常用的请求分配算法,在此基础上提出了最短响应时间优先调度算法。仿真表明,该算法具有很好的调度效果和很高的稳定性。     

基于PI控制律的通用递阶模糊控制器

为解决常规模糊控制器存在的通用性和工程简便性问题,针对动态特性随操作条件变化对象建立自适应递阶模糊控制器,实现闭环模糊增益调度,并引入稳定监督控制使控制系统具有工程稳定性。