Inductive logic programming
43 papers with code • 1 benchmarks • 2 datasets
Libraries
Use these libraries to find Inductive logic programming models and implementations
Kinship
RuDaS
Most implemented papers
Probabilistic Inductive Logic Programming Based on Answer Set Programming
We propose a new formal language for the expressive representation of probabilistic knowledge based on Answer Set Programming (ASP).
Online Learning of Event Definitions
The Event Calculus is a temporal logic that has been used as a basis in event recognition applications, providing among others, direct connections to machine learning, via Inductive Logic Programming (ILP).
Distributed Online Learning of Event Definitions
Logic-based event recognition systems infer occurrences of events in time using a set of event definitions in the form of first-order rules.
Incremental and Iterative Learning of Answer Set Programs from Mutually Distinct Examples
This paper is under consideration for acceptance in
Playgol: learning programs through play
In this approach, a program induction system (the learner) is given a set of tasks and initial background knowledge.
Neural Logic Reinforcement Learning
Deep reinforcement learning (DRL) has achieved significant breakthroughs in various tasks.
Induction of Non-Monotonic Rules From Statistical Learning Models Using High-Utility Itemset Mining
We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models.
Inductive Logic Programming via Differentiable Deep Neural Logic Networks
apayani/ILP
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In particular, we show that our proposed method outperforms the state of the art ILP solvers in classification tasks for Mutagenesis, Cora and IMDB datasets.
Towards meta-interpretive learning of programming language semantics
We introduce a new application for inductive logic programming: learning the semantics of programming languages from example evaluations.
RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools
Logical rules are a popular knowledge representation language in many domains, representing background knowledge and encoding information that can be derived from given facts in a compact form.
