Solving computational learning problems of boolean formulae on DNA computers

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

We apply a DNA-based massively parallel exhaustive search to solving the computational learning problems of DNF (disjunctive normal form) Boolean formulae. Learning DNF formulae from examples is one of the most important open problems in computational learning theory and the problem of learning 3-term DNF formulae is known as intractable if RP 6 ≠ NP. We propose new methods to encode any k-term DNF formula to a DNA strand, evaluate the encoded DNF formula for a truth-value assignment by using hybridization and PCR, and find a consistent DNF formula with the given examples. By employing these methods, we show that the class of k-term DNF formulae (for any constant k) and the class of general DNF formulae are eficiently learnable on DNA computer.

本文言語English
ホスト出版物のタイトルDNA Computing - 6th International Workshop on DNA-Based Computers, DNA 2000 Leiden, The Netherlands, June 13-17, 2000 Revised Papers
編集者Grzegorz Rozenberg, Anne Condon
出版社Springer Verlag
ページ220-230
ページ数11
ISBN(印刷版)3540420762, 9783540420767
DOI
出版ステータスPublished - 2001 1 1
外部発表はい
イベント6th International Workshop on DNA-Based Computers, DNA 2000 - Leiden, Netherlands
継続期間: 2000 6 132000 6 17

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2054
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other6th International Workshop on DNA-Based Computers, DNA 2000
CountryNetherlands
CityLeiden
Period00/6/1300/6/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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