article

Learning Conjunctions of Horn Clauses

Authors:

Dana Angluin,

Michael Frazier,

Leonard PittAuthors Info & Claims

Machine Learning, Volume 9, Issue 2-3

Pages 147 - 164

https://doi.org/10.1007/BF00992675

Published: 01 July 1992 Publication History

Publisher Site

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.

Cited By

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Blum SKoudijs ROzaki ATouileb S(2024)Learning Horn envelopes via queries from language modelsInternational Journal of Approximate Reasoning10.1016/j.ijar.2023.109026171:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.ijar.2023.109026
Kučera P(2022)Learning a Propagation Complete FormulaIntegration of Constraint Programming, Artificial Intelligence, and Operations Research10.1007/978-3-031-08011-1_15(214-231)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-08011-1_15
Chen HValeriote M(2021)Learnability of solutions to conjunctive queriesThe Journal of Machine Learning Research10.5555/3322706.336200820:1(2422-2449)Online publication date: 9-Mar-2021
https://dl.acm.org/doi/10.5555/3322706.3362008
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Index Terms

Learning Conjunctions of Horn Clauses
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Logic programming and answer set programming
  2. Machine learning
2. Theory of computation
  1. Logic
    1. Constraint and logic programming

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Information & Contributors

Information

Published In

Machine Language Volume 9, Issue 2-3

Computational learning theory

July 1992

167 pages

ISSN:0885-6125

Editors:
Jaime G. Carbonnell
Carnegie Mellon Univ., Pittsburgh, PA
,
Thomas Dietterich
Oregon State Univ., Corvallis
,
John Case
Univ. of Delaware, Newark
,
Anselm Blumer
Tufts Univ., Medford, MA

Issue’s Table of Contents

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 July 1992

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Cited By

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Blum SKoudijs ROzaki ATouileb S(2024)Learning Horn envelopes via queries from language modelsInternational Journal of Approximate Reasoning10.1016/j.ijar.2023.109026171:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.ijar.2023.109026
Kučera P(2022)Learning a Propagation Complete FormulaIntegration of Constraint Programming, Artificial Intelligence, and Operations Research10.1007/978-3-031-08011-1_15(214-231)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-08011-1_15
Chen HValeriote M(2021)Learnability of solutions to conjunctive queriesThe Journal of Machine Learning Research10.5555/3322706.336200820:1(2422-2449)Online publication date: 9-Mar-2021
https://dl.acm.org/doi/10.5555/3322706.3362008
Bansal SKailasam SObiedkov S(2021)Approximate Computation of Exact Association RulesFormal Concept Analysis10.1007/978-3-030-77867-5_7(107-122)Online publication date: 29-Jun-2021
https://dl.acm.org/doi/10.1007/978-3-030-77867-5_7
Hermo MOzaki A(2020)Exact LearningACM Transactions on Computation Theory10.1145/336993012:1(1-25)Online publication date: 11-Feb-2020
https://dl.acm.org/doi/10.1145/3369930
Borchmann DHanika TObiedkov S(2020)Probably approximately correct learning of Horn envelopes from queriesDiscrete Applied Mathematics10.1016/j.dam.2019.02.036273:C(30-42)Online publication date: 15-Feb-2020
https://dl.acm.org/doi/10.1016/j.dam.2019.02.036
Tsouros DStergiou K(2020)Efficient multiple constraint acquisitionConstraints10.1007/s10601-020-09311-425:3-4(180-225)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s10601-020-09311-4
Ozaki A(2020)On the Complexity of Learning Description Logic OntologiesReasoning Web. Declarative Artificial Intelligence10.1007/978-3-030-60067-9_2(36-52)Online publication date: 24-Jun-2020
https://dl.acm.org/doi/10.1007/978-3-030-60067-9_2
Picado JTermehchy AFern AAtaei P(2019)Logical scalability and efficiency of relational learning algorithmsThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-018-0523-828:2(147-171)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s00778-018-0523-8
Obiedkov S(2019)Learning Implications from Data and from QueriesFormal Concept Analysis10.1007/978-3-030-21462-3_3(32-44)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1007/978-3-030-21462-3_3
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