Inductive Logic Programming

• Inductive logic programming is the subfield of machine learning that uses  first-order logic to represent hypotheses and data. Because first-order logic is expressive and declarative, inductive logic programming specifically targets problems involving structured data and background knowledge. Inductive logic programming tackles a wide variety of problems in machine learning, including classification, regression, clustering, and reinforcement learning, often using “upgrades” of existing propositional machine learning systems. It relies on logic for knowledge representation and reasoning purposes. Notions of coverage, generality, and operators for traversing the space of hypotheses are grounded in logic, see also  logic of generality. Inductive logic programming systems have been applied to important applications in bio- and chemo-informatics, natural language processing,...

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

Learning in logic; Multi-relational data mining; Relational data mining; Relational learning

Publication and Content Type

vet (subject category)

kap (subject category)