Expert maintenance systems in telecommunication networks

Our survey of some 40 network maintenance expert systems reveals theri main shortcoming, which is the difficulty to acquire troubleshooting knowledge both when initializing the expert system and after its deployment. Additionally, the state-of-the-art troubleshooting expert systems do not optimize troubleshooting cost. We present theAO ^* algorithm to generate a network troubleshooting expert system which minimizes the expected troubleshooting cost and learns better troubleshooting techniques during its operation.     

Truth maintenance systems and their application for verifying Expert System Knowledge Bases

Truth maintenance systems (TMSs) were introduced more than ten years ago, but recently there is an explosion of interest in them and their possible applications in different areas. In this paper we discuss truth maintenance from three perspectives:

· Truth maintenance as a data base management facility, which was in fact the original intention of the TMS.

· Truth maintenance as an inference facility, which provides a way to extend the role of the TMS in solving problems.

· Truth maintenance as a verification facility, which illustrates a new and promising application of TMSs in the area of expert systems design.

This paper is not intended to provide a complete survey on TMSs, rather it aims to present the basic ideas and functionality of TMS, and to show how different kinds of TMS can be used as a meta-environment for testing Expert System Knowledge Bases, represented as sets of production rules, for anomalies. The paper is addressed to two groups of readers: those who are looking for an introductory survey on TMSs, and those who are interested in non-conventional techniques for Expert System Knowledge Base verification.     

Expert systems for engineering design

Abstract: An expert system embodies a humun expert's domain-specific knowledge and skill, acquired and refined over years of experience. A number of problems in diagnosis and engineering design can be solved by Using current expert-system techniques. This paper enumerates the main components of such problems and the steps that are taken in solving them. A few prototypical articificial intellegence systems embody techniques that can be applied to engineering problems. These are surveyed, and their relevance to components of design problems is discussed. Some expert systems in design domains are summarized, with emphasis on aspects that can illustrate wider applicability of the techniques. A number of avenues of further research are evident, and the area of engineering design offers rich opportunities for advancing the state-of-the-art in expert systems. An annotated selective bibliography is included     

Expert systems for small businesses

Small business contribute significantly to the economy. New information system technologies, like expert systems have the promise of improving the efficiency and competitiveness of small businesses. This paper reviews the issues related to application of expert systems in a small business and discusses their capabilities and limitations. The role of decision support systems and integration of DSS and expert systems as a useful tool for small businesses is also examined. Further, the issues concerning the selection of expert systems for a small business are described.     

Expert systems for cancer chemotherapy

In the present paper we describe BREASTCAN and NEWCHEM, two expert systems for the characterization of optimal adjuvant cancer therapies. The purpose of BREASTCAN is to support physicians in the postoperative breast cancer therapy, on the basis of currently used therapy protocols. It was developed in Prolog and positively validated, referring to the chemotherapies used by oncologists for some patients in the National Cancer Institute in Milan. NEWCHEM is a system oriented to the development of new cancer therapies, based on pharmaco-cell kinetic modeling and the newest molecular knowledge about neoplastic process. The system is being built and at first it will be validated by experiments on mice. Our aim with NEWCHEM is to extend our knowledge base and our rules to incorporate also all the modt advanced knowledge at the molecular and cellular level, both theoretical and experimental, to make readily accessible to the health-community a system was the present state of the art allows.     

Expert systems for inventory control management

An expert system for inventory management is presented in this paper. The focus is on the development of a simple, user friendly tool that can be used by managers to increase the effectiveness of their inventory control systems. The expert system is capable of deriving input parameters by performing necessary analysis on databases, implementing a set of rules for the selection of inventory models, and present the output through tables. plots, or graphs. The scope of this paper is limited to the single item, single location problem.     

Expert systems for legal decision making

Abstract: AI technology is being used to develop expert systems that solve complex problems in the legal area. Most of these systems employ rules to describe the strategies and procedures used by litigators to analyze legal issues. The tasks performed by these systems include interpreting the law, anticipating the legal consequences of proposed actions, predicting the effects of changes in legislation, as well as analyzing and managing cases. The special characteristics of the legal domain cause certain problems for expert system builders. We discuss some of these problems and describe LDS and SAL, two expert systems we have developed for case evaluation and settlement in the product liability area. SAL (System for Asbestos Litigation) evolved from the earlier and more general expert system, LDS (Legal Decisionmaking System). We also describe XPL, an explanation facility we developed for use by SAL and other expert system applications.     

Expert database systems

An overview and some impressions are given of the first conference on Expert Database Systems in Charleston, April 1986.The emphasis in this overview is on the keynote address, the invited lecture and the discussions in the panels, because these were not published in the proceedings.     

一种多机器人系统仿真平台的框架结构研究

针对多机器人系统实验平台造价高,硬件容易老化、损坏等问题,提出一种仿真平台实现模拟的框架结构。仿真平台基于客户机／服务器结构,利用内核模块管理其他功能模块,引入插件概念构造传感器插件有效的实现了传感器的模拟。实验证明其易用性与实用性。     

Expert systems integrated with information systems

Amongst the users of the AIDA applications there is a rapidly growing interest in the use of expert systems, not as independent systems, but as logical extensions of their already existing information systems. In this paper a prototype system (IDEA) will be described that consists of a set of utilities for the construction of an expert system within the context of an AIDA application. Although IDEA does not excel in sophisticated knowledge representations nor in search strategies (the development of which was not our primary concern) it is able to demonstrate that the facilities provided by AIDA together with the IDEA facilities result in an expert system which is characterized by a high degree of integration with the already operational information system.     

Expert systems and optimization

A problem-solving approach involving the integration of expert systems and optimization techniques is presented. A class of expert systems called tandem expert systems is introduced. Three variants of the tandem expert system, the data-reducing, model-based, and model-modifying expert systems, are explained with examples. It is emphasized that optimization techniques can be used more frequently in future expert systems