Logica is a logic programming language that compiles to SQL. It runs on DuckDB, Google BigQuery, PostgreSQL and SQLite.

The Power of Prolog: Introduction to modern Prolog

SWI-Prolog Main development repository

Soufflé is a variant of Datalog for tool designers crafting analyses in Horn clauses. Soufflé synthesizes a native parallel C++ program from a logic specification.

Tools for transparent data transformation

The OpenCog (hyper-)graph database and graph rewriting system

High performance, concurrent functional programming abstractions

🦉 A grounder and solver for logic programs.

Neuro-Symbolic AI with Knowledge Graph 🌱🐋🌍

The only reasonable scripting engine for Go.

A declarative programming framework

📝 Web-based, reactive Datalog notebooks for data analysis and visualization

An open source Prolog interpreter in JavaScript

PySwip is a Python-Prolog interface that enables querying SWI-Prolog in your Python programs.

Logic programming in Rust

Datalog compiler embedded in Rust as a procedural macro

Rust bindings for the Z3 solver.

Logtalk - declarative object-oriented logic programming language

An interpreter for learning and exploring pure λ-calculus

Mejora tu lógica de programación y aprende mucho más resolviendo estos ejercicios.

Shen language kernel sources for porters

An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.

Deep Learning and Logical Reasoning from Data and Knowledge

An explainable inference software supporting annotated, real valued, graph based and temporal logic

Ciao is a modern Prolog implementation that builds up from a logic-based simple kernel designed to be portable, extensible, and modular.

A reference library for constraint-solving with propagators and CDCL.

PyNeuraLogic lets you use Python to create Differentiable Logic Programs

Implementation for the Neural Logic Machines (NLM).

An in-memory datalog implementation for OCaml.

✨✨Latest Advances on Neuro-Symbolic Learning in the era of Large Language Models