dissertation · 2018

INDUCTIVE EQUATIONAL LOGIC PROGRAMMING

Cited by 0Open access

Abstract

Inductive Logic Programming (ILP) is an area of research that is at the intersection of Machine Learning and Logic Programming. An ILP system uses positive and negative facts (examples) and optional background knowledge to induce a logic program that 1) accurately describes the facts and 2) successfully predicts the outcome of unseen examples. This thesis introduces a new ILP algorithm implemented in Equational Logic that takes a hybrid approach to induction, using bottom-up generalization combined with inverse narrowing to create recursive equations. We also introduce a framework for the induction of conditional equations from positive ground examples.

Cite this paper

APA 7

McDonald, A. B. (2018). INDUCTIVE EQUATIONAL LOGIC PROGRAMMING. https://doi.org/10.23860/diss-mcdonald-arthur-2018

MLA 9

McDonald, A. B. “INDUCTIVE EQUATIONAL LOGIC PROGRAMMING.” 2018, https://doi.org/10.23860/diss-mcdonald-arthur-2018.

Chicago

McDonald, A. B. 2018. “INDUCTIVE EQUATIONAL LOGIC PROGRAMMING.” https://doi.org/10.23860/diss-mcdonald-arthur-2018.

Harvard

McDonald, A.B. (2018) ‘INDUCTIVE EQUATIONAL LOGIC PROGRAMMING’. Available at: https://doi.org/10.23860/diss-mcdonald-arthur-2018.

BibTeX

@phdthesis{mcdonald2018inductive,
  title = {{INDUCTIVE EQUATIONAL LOGIC PROGRAMMING}},
  author = {McDonald, A. B.},
  year = {2018},
  doi = {10.23860/diss-mcdonald-arthur-2018}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.