Generative artist and programmer David Bollinger uses math and algorithms to create artwork. This illustration reflects n-unit cubes recursively subdivided based on patterns defined by the greatest ...

Abstract: Probabilistic logic programming extends logic programming by enabling the representation of uncertain information by means of probability theory. Probabilistic logic programming is at the ...

Inductive logic programming (ILP) studies the learning of (Prolog) logic programs and other relational knowledge from examples. Most machine learning algorithms are restricted to finite, propositional ...

For individuals with an interest in Logic Programming, this repository serves as an easy-to-use playground, eliminating the hassle of complex environment setup. To utilize this repository, please use ...

Inductive logic programming (ILP) and machine learning together represent a powerful synthesis of symbolic reasoning and statistical inference. ILP focuses on deriving interpretable logic rules from ...

Abstract: Incorporating the possibility of attaching attributes to variables in a logic programming system has been shown to allow the addition of general constraint solving capabilities to it. This ...