Published 1994 | Version v1
Miscellaneous Restricted

Deep knowledge and knowledge compilation for dynamic systems

  • 1. Osaka Univ., Ibaraki (Japan). Inst. of Scientific and Industrial Research

Description

Expert systems are viewed as knowledge-based systems which efficiently solve real-world problems based on the expertise contained in their knowledge bases elicited from domain experts. Although such expert systems that depends on heuristics of domain experts have contributed to the current success, they are known to be brittle and hard to build. This paper is concerned with research on model-based diagnosis and knowledge compilation for dynamic systems conducted by the author's group to overcome these difficulties. Firstly, we summarize the advantages and shortcomings of expert systems. Secondly, deep knowledge and knowledge compilation is discussed. Then, latest results of our research on model-based diagnosis is overviewed. The future direction of knowledge base technology research is also discussed. (author)

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Part of:
Proceedings of specialists' meeting on application of artificial intelligence and robotics to nuclear plants

Additional details

Publishing Information

Imprint Title
Proceedings of specialists' meeting on application of artificial intelligence and robotics to nuclear plants
Imprint Pagination
431 p.
Journal Page Range
p. 59-70.
Report number
INIS-JP--027

Conference

Title
specialists' meeting on application of artificial intelligence and robotics to nuclear plants.
Acronym
AIR'94
Dates
30 May - 1 Jun 1994.
Place
Tokai, Ibaraki (Japan).

INIS

Country of Publication
Japan
Country of Input or Organization
Japan
INIS RN
26047477
Subject category
S22: GENERAL STUDIES OF NUCLEAR REACTORS;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ARTIFICIAL INTELLIGENCE; DATA COMPILATION; DESIGN; DIAGNOSIS; EXPERT SYSTEMS; KNOWLEDGE BASE; PROGRAMMING LANGUAGES; SIMULATION

Optional Information