Presentation 2002/5/17
Consideration about Learning from Interpretations in General Clausal Theory
Noriaki YAMASAKI, Katumi INOUE, Hiromasa HANEDA,
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Abstract(in English) In the framework of inductive logic programming, learning from interpretations which takes an inter-pretation as an example is proposed. However, a perfect interpretation may not always be given and the truth value to each ground atoms in the Herbrand base may be partially given. Then, in this reserch, we focus on lerning from partial interpretations which takes not only complete interpretations as but partial interpretations as examples. We propose an algotithm of learning from partial interpretations. The proposed algorithm enables us to perform inductive learning under incomplete information.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) inductive logic programming / learning from interpretations / partial interpretations
Paper # AI2002-12
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Committee AI
Conference Date 2002/5/17(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Consideration about Learning from Interpretations in General Clausal Theory
Sub Title (in English)
Keyword(1) inductive logic programming
Keyword(2) learning from interpretations
Keyword(3) partial interpretations
1st Author's Name Noriaki YAMASAKI
1st Author's Affiliation Department of Electrical and Electoronics Engineering, Kobe University()
2nd Author's Name Katumi INOUE
2nd Author's Affiliation Department of Electrical and Electoronics Engineering, Kobe University
3rd Author's Name Hiromasa HANEDA
3rd Author's Affiliation Department of Electrical and Electoronics Engineering, Kobe University
Date 2002/5/17
Paper # AI2002-12
Volume (vol) vol.102
Number (no) 91
Page pp.pp.-
#Pages 5
Date of Issue