書誌事項
- タイトル別名
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- A Method of Machine Discovery Based on Geometric Constraints
- ケイサンキ ニヨル ズケイテキ セイヤク ニ モトズク ハッケン シュホウ
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説明
<p>This paper describes a new method of discovering theorems in a plane geometry domain. In order to discover useful theorems from a figure, the following subjects should be discussed : the contents of acquired data by observing the figure, the techniques for avoiding combinatorial explosion of expressions, and the criteria for choosing useful theorems from generated expressions. Our discovery method is based on the sides in a given figure. All the geometric relations among sides are observed from a figure. Deduced expression which shows the relation of closely located sides in the figure are regarded as a useful theorem. It is because a human often considers such an expression to be an important theorem. Observed geometric relations among sides are used for both choosing useful theorems and avoiding combinatorial explosion of generated expressions. Although most of the methods of previous discovery systems such as AM, KEKADA and IDS require much initial knowledge for evaluating the usefulness of generated knowledge, our method needs little initial knowledge about plane geometry. Our discovery method has been implemented in a system called PLANET, a discovery system for plane geometry theorems. PLANET has succeeded in discovering many useful geometry theorems and trigonometric formulas, including Menelaus' theorem, Ceva's theorem, and addition theorems of trigonometric functions, through trial and error.</p>
収録刊行物
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- 人工知能
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人工知能 11 (6), 960-967, 1996-11-01
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390285697602201344
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- NII論文ID
- 110002807997
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- NII書誌ID
- AN10067140
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- ISSN
- 09128085
- 24358614
- 21882266
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- NDL書誌ID
- 4066059
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDLサーチ
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可