An adaptive model-based diagnostic system:
Abstract: "This paper describes an experimental diagnostic system which explores adaptability with learning capability from its experience. It takes a model based reasoning approach, utilizing experiential knowledge at the same time. Experiential knowledge consists of cached symptom-failure ass...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Tokyo, Japan
1990
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| Series: | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum
957 |
| Subjects: | |
| Summary: | Abstract: "This paper describes an experimental diagnostic system which explores adaptability with learning capability from its experience. It takes a model based reasoning approach, utilizing experiential knowledge at the same time. Experiential knowledge consists of cached symptom-failure association rules and a probability model of the target system components. It is able to generate and select appropriate tests according to the failure probability distribution. With this capability, when the system has had a similar experience in the past, it can diagnose the failure faster and more efficiently by suggesting better tests Therefore, this system gives a solution to both the knowledge acquisition bottleneck problem of rule-based systems and the efficiency problem of model-based systems. It is being implemented in ESP language on a prolog machine PSI-II. The effectiveness of the technique is shown by an experimental result. |
| Physical Description: | 6 S. |
Staff View
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| 490 | 1 | |a Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |v 957 | |
| 520 | 3 | |a Abstract: "This paper describes an experimental diagnostic system which explores adaptability with learning capability from its experience. It takes a model based reasoning approach, utilizing experiential knowledge at the same time. Experiential knowledge consists of cached symptom-failure association rules and a probability model of the target system components. It is able to generate and select appropriate tests according to the failure probability distribution. With this capability, when the system has had a similar experience in the past, it can diagnose the failure faster and more efficiently by suggesting better tests | |
| 520 | 3 | |a Therefore, this system gives a solution to both the knowledge acquisition bottleneck problem of rule-based systems and the efficiency problem of model-based systems. It is being implemented in ESP language on a prolog machine PSI-II. The effectiveness of the technique is shown by an experimental result. | |
| 650 | 4 | |a Debugging in computer science | |
| 650 | 4 | |a Knowledge acquisition (Expert systems) | |
| 650 | 4 | |a Rule-based programming | |
| 700 | 1 | |a Nakakuki, Yoichiro |e Verfasser |4 aut | |
| 700 | 1 | |a Tanaka, Midori |e Verfasser |4 aut | |
| 830 | 0 | |a Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |v 957 |w (DE-604)BV010943497 |9 957 | |
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Record in the Search Index
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| author | Koseki, Yoshiyuki Nakakuki, Yoichiro Tanaka, Midori |
| author_facet | Koseki, Yoshiyuki Nakakuki, Yoichiro Tanaka, Midori |
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| id | DE-604.BV010972609 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T18:01:55Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007342010 |
| oclc_num | 25854266 |
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| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | 6 S. |
| publishDate | 1990 |
| publishDateSearch | 1990 |
| publishDateSort | 1990 |
| record_format | marc |
| series | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |
| series2 | Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum |
| spelling | Koseki, Yoshiyuki Verfasser aut An adaptive model-based diagnostic system by Y. Koseki, Y. Nakakuki & M. Tanaka Tokyo, Japan 1990 6 S. txt rdacontent n rdamedia nc rdacarrier Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum 957 Abstract: "This paper describes an experimental diagnostic system which explores adaptability with learning capability from its experience. It takes a model based reasoning approach, utilizing experiential knowledge at the same time. Experiential knowledge consists of cached symptom-failure association rules and a probability model of the target system components. It is able to generate and select appropriate tests according to the failure probability distribution. With this capability, when the system has had a similar experience in the past, it can diagnose the failure faster and more efficiently by suggesting better tests Therefore, this system gives a solution to both the knowledge acquisition bottleneck problem of rule-based systems and the efficiency problem of model-based systems. It is being implemented in ESP language on a prolog machine PSI-II. The effectiveness of the technique is shown by an experimental result. Debugging in computer science Knowledge acquisition (Expert systems) Rule-based programming Nakakuki, Yoichiro Verfasser aut Tanaka, Midori Verfasser aut Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum 957 (DE-604)BV010943497 957 |
| spellingShingle | Koseki, Yoshiyuki Nakakuki, Yoichiro Tanaka, Midori An adaptive model-based diagnostic system Shin-Sedai-Konpyūta-Gijutsu-Kaihatsu-Kikō <Tōkyō>: ICOT technical memorandum Debugging in computer science Knowledge acquisition (Expert systems) Rule-based programming |
| title | An adaptive model-based diagnostic system |
| title_auth | An adaptive model-based diagnostic system |
| title_exact_search | An adaptive model-based diagnostic system |
| title_full | An adaptive model-based diagnostic system by Y. Koseki, Y. Nakakuki & M. Tanaka |
| title_fullStr | An adaptive model-based diagnostic system by Y. Koseki, Y. Nakakuki & M. Tanaka |
| title_full_unstemmed | An adaptive model-based diagnostic system by Y. Koseki, Y. Nakakuki & M. Tanaka |
| title_short | An adaptive model-based diagnostic system |
| title_sort | an adaptive model based diagnostic system |
| topic | Debugging in computer science Knowledge acquisition (Expert systems) Rule-based programming |
| topic_facet | Debugging in computer science Knowledge acquisition (Expert systems) Rule-based programming |
| volume_link | (DE-604)BV010943497 |
| work_keys_str_mv | AT kosekiyoshiyuki anadaptivemodelbaseddiagnosticsystem AT nakakukiyoichiro anadaptivemodelbaseddiagnosticsystem AT tanakamidori anadaptivemodelbaseddiagnosticsystem |