Deep knowledge and knowledge compilation for dynamic systems
Creators
- 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)
Files
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