Many expert systems have moved out of development laboratories into field test and routine use. About sixty such systems are listed. Academic research laboratories are contributing manpower to fuel the commercial development of AI. But the quantity of AI research may decline as a result unless the applied systems are experimented with and analyzed.

/pdf/expert-systems-working-systems-and-the-research-literature-4e2u8p4e17.pdf

Expert systems: working systems and the research literature

Knowledge-based expert systems in structural design

Trends in engineering software and hardwareKnowledge-based expert systems in structural design

An analysis of survey data collected from a sample of 98 Fortune 500 industrial companies reveals that expert systems (ESs) are utilized in manufacturing by 52 per cent of the companies, among which ESs are perceived to be more useful in process planning, product design, layout, facility design and maintenance; and less useful in forecasting production demand and reducing accidents/ safety hazards. Some suggestions are offered on integrating ESs with simulation and logistical knowledge, and involving top management in ES development projects to maximize the pay‐off of utilizing ESs in manufacturing.

Utilization and Benefits of Expert Systems in Manufacturing

Production rule schemes have proven quite effective in concisely representing expert knowledge in several application areas. Yet, there are many problems for which one would like to take advantage of additional knowledge that may not be easily represented in these surface level models. One class of problems of particular practical interest are those in which we would like to have a computer-based system give interactive advice on how to control and interpret results from a set of complex and interrelated applications programs. The advice may refer to interpretations of current results, possible experiments that should be performed with the help of the applications programs, and indications of inconsistencies in specific analytical procedures and in problem solving sequences followed by the user. In the present paper we report on our experiences in designing an expert system (ELAS), of the type described above, for well log analysis in oil exploration and production. We have integrated a production rule advice model (using the EXPERT system) with existing Amoco software for well-log analysis and display. In doing so, the original system for well-log analysis was reorganized so that its use could be monitored and controlled, and its knowledge structured according to the types and sequences of methods used by expert analysts. By varying the assumptions and parameters used in the different individual analyses, our goal is to make available interactive interpretations of the alternative approaches that an expert might take to a complex problem of well-log analysis.

/pdf/building-expert-systems-for-controlling-complex-programs-495ym7wfzg.pdf

Building expert systems for controlling complex programs

We are concerned with two important issues in simulation modelling: model comprehension and model construction. Model comprehension is limited because many important choices taken during the modelling process are not documented. This makes it difficult for models to be modified or used by others. A key factor hindering model construction is the vast modelling search space which must be navigated. This is exacerbated by the fact that many modellers are unfamiliar with the terms and concepts catered to by current tools. The root of both problems is the lack of facilities for representing or reasoning about domain concepts in current simulation technology. The basis for our achievements in both of these areas is the development of a language with two distinct levels; one for representing domain information, and the other for representing the simulation model. Of equal importance, is the fact that we make formal connections between these two levels. The domain we are concerned with is ecological modelling. This language, called Elklogic, is based on the typed lambda calculus. Important features include a rich type structure, the use of various higher order functions, and semantics. This enables complex expressions to be constructed from relatively few primitives. The meaning of each expression can be determined in terms of the domain, the simulation model, or the relationship between the two. We describe a novel representation for sets and substructure, and a variety of other general concepts that are especially useful in the ecological domain. We use the type structure in a novel way: for controlling the modelling search space, rather than a proof search space. We facilitate model comprehension by representing modelling decisions that are embodied in the simulation model. We represent the simulation model separately from, but in terms of a domain mode. The explicit links between the two models constitute the modelling decisions. The semantics of Elklogic enables English text to be generated to explain the simulation model in domain terms.

https://ntrs.nasa.gov/api/citations/19930008337/downloads/19930008337.pdf

The use of typed lambda calculus for comprehension and construction of simulation models in the domain of ecology

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Michael Uschold

Author Tools

Chat about Author

Papers

Building expert systems for controlling complex programs

The use of typed lambda calculus for comprehension and construction of simulation models in the domain of ecology