ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    facet.materialart.
    Unknown
    Functional reasoning in diagnostic problem solving (1988)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA, Marshall Space Flight Center, Fourth Conference on Artificial Intelligence for Space Applications; p 29-38
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
  • 2
    facet.materialart.
    Unknown
    Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems (1988)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA, Marshall Space Flight Center, Fourth Conference on Artificial Intelligence for Space Applications; p 271-279
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
  • 3
    facet.materialart.
    Unknown
    Using output to evaluate and refine rules in rule-based expert systems (1987)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: The techniques described provide an effective tool which knowledge engineers and domain experts can utilize to help in evaluating and refining rules. These techniques have been used successfully as learning mechanisms in a prototype adaptive diagnostic expert system and are applicable to other types of expert systems. The degree to which they constitute complete evaluation/refinement of an expert system depends on the thoroughness of their use.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA. Marshall Space Flight Center, Third Conference on Artificial Intelligence for Space Applications, Part 1; p 9-13
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    NASA TECHNICAL REPORTS
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...