### Abstract

An algorithm is presented for learning the class of Boolean formulas that are expressible as conjunctions of Horn clauses. (A Horn clause is a disjunction of literals, all but at most one of which is a negated variable.) The algorithm uses equivalence queries and membership queries to produce a formula that is logically equivalent to the unknown formula to be learned. The amount of time used by the algorithm is polynomial in the number of variables and the number of clauses in the unknown formula.

Original language | English (US) |
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Pages (from-to) | 147-164 |

Number of pages | 18 |

Journal | Machine Learning |

Volume | 9 |

Issue number | 2 |

DOIs | |

State | Published - Jul 1992 |

### Keywords

- Propositional Horn sentences
- equivalence queries
- exact identification
- membership queries
- polynomial time learning

### ASJC Scopus subject areas

- Software
- Artificial Intelligence

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## Cite this

Angluin, D., Frazier, M., & Pitt, L. (1992). Learning Conjunctions of Horn Clauses.

*Machine Learning*,*9*(2), 147-164. https://doi.org/10.1023/A:1022689015665