一类提取模糊规则的新方法及其在干燥建模中的应用

基于系统的输入－输出数据,提出一种通过划分输入空间撮模糊规则的方法,并将该方法应用于建模非线性程度较高物干燥过程。建模过程中,首先利用训练样本将输入空间动态地划分为若干个子空间,然后针对第一个子空间了生一条模糊规则,再将所产生的模糊规则共成一个模糊规则库,模糊逻辑系统的最终输出从模糊规则库中产生。仿真结果表明,该方法可很好地预测干燥系统的物料降水率,而且简单实用,十分可靠。     

Designing Agent-Based Electronic Employment Markets

Two modes of matching people with jobs prevail at present: 1) hierarchical planning and 2) distributed markets. Each has strengths and limitations, but few systems have been designed to take advantage of strengths corresponding to both. With evolving information technology, however, the job-matching process could be accomplished far more equitably and efficiently using web-based markets within the firm, and intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). Through the research described in this paper, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This paper integrates the key economic and technological elements required to design robust electronic employment markets. And the corresponding research provides new knowledge and insight into co-development of the requisite economic markets and agent technologies.     

Building Agile Systems with Mobile Code

Mobile code has been championed as a solution to a plethora of software problems. This paper describes investigative work undertaken in order to evaluate the mobile code abstractions of Mobile Agents and Mobile Objects, and to understand the implications of using these abstractions to build distributed systems.We describe two systems built to support the Sales Order Process of a distributed manufacturing enterprise, using IBM's Aglets Software Development Kit. The Sales Order Process model and the requirements for agility used as the basis for these implementations are derived from data collected in an industrial case study.Both systems are evaluated using the Goal/Question/Metric methodology. Two new metrics for Semantic Alignment and Change Capability are presented and used to evaluate each system with respect to the degree of system agility supported. The systems are evaluated through a set of scenarios generated during the case study in an attempt to see if they support system integration and agility in the manufacturing domain. Further we examine the implications of using a mobile code abstraction when compared with the abstraction offered by traditional distribution technology.The work described provides evidence that both Mobile Agent and Mobile Object systems have inherent properties that can be used to build agile distributed systems. Further, Mobile Agents with their additional autonomy provide marginally greater support.     

Decision-Centric Information Monitoring

We are interested in information management for decision support applications, especially those that monitor distributed, heterogeneous databases to assess time-critical decisions. Users of such applications can easily be overwhelmed with data that may change rapidly, may conflict, and may be redundant. Developers are faced with a dilemma: either filter out most information and risk excluding critical items, or gather possibly irrelevant or redundant information, and overwhelm the decision maker. This paper describes a solution to this dilemma called decision-centric information monitoring (DCIM). First, we observe that decision support systems should monitor only information that can potentially change some decision. We present an architecture for DCIM that meets the requirements implied by this observation. We describe techniques for identifying the highest value information to monitor and techniques for monitoring that information despite autonomy, distribution, and heterogeneity of data sources. Finally, we present lessons learned from building LOOKOUT, which is to our knowledge the first implementation of a top-to-bottom system performing decision-centric information monitoring.     

A hierarchical, agent-based service oriented architecture for smart environments

Service Oriented Architectures, which allow for the integration of different subsystems and of applications running on different devices and platforms, may be very suitable to solve the problem of service personalization in large smart environments like cities, where the number of potential users and potentially available services is rapidly growing. Taking this into account, we have designed an agent-based service oriented architecture for smart spaces. Two of the greatest challenges in the design of such a solution are providing effective device, service and context federation and composition mechanisms and handling user mobility. For the first challenge, we have designed a hierarchical architecture and developed a set of inheritance, aggregation and access mechanisms for devices, services and context. To handle user mobility, we have followed three different strategies, using stationary, mobile or nomadic agents. In this paper, we describe the main aspects of our architecture and perform an experimental evaluation to determine the advantages and drawbacks of the different strategies.     

Modeling expert problem solving in a game of chance: a Yahtzee© case study

Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem-solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.     

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.     

Towards a Mobile Code Management Environment for Complex,Real-Time,Distributed Systems

We present a novel mobile code management environment,currently under design and development. Our design employs anopen architecture, suitable for ``plug-and-play' with COTS andother groups' tools. While we have studied new algorithms, costand objective functions, and other fundamental issues, the maincontribution of this experimental research work is in the environmentitself. It should be noted that networked platforms, such asthe World Wide Web, are inherently not suitable for traditional,predictable real-time applications. Thus, real-time concernsnecessarily need to be blended with others concerns, and thetarget applications, making use of our environment, will toobe a blend of partially hard real-time and partially (or mostly)soft-real- time ones. The prototype environment will thereforesupport performance-based analysis and management focusing notonly on predictability but also on compilation, efficiency, safetyand other tradeoffs. We have selected the Java language and itsbytecode format as a representation for mobile code as well asa language for our implementation.