Name: Active Inference in Prolog
Author: ActiveInferenceInstitute

Imported from ActiveInferenceInstitute/Active_InferAnts (0_CONTEXT/Computer_Languages/Prolog/SKILL.md). Install upstream with npx skills add ActiveInferenceInstitute/Active_InferAnts --skill Prolog. Copyright stays with the author.

Active Inference in Prolog

Overview

This skill provides a complete Active Inference implementation in Prolog, demonstrating Bayesian belief updating, variational free energy calculation, and expected free energy-based policy selection.

Core Algorithms

Belief Updating: Bayesian inference using observation likelihoods to update posterior beliefs
Free Energy Calculation: KL divergence between posterior beliefs and prior distribution
Policy Selection: Softmax action selection over expected free energy per action
Perception-Action Loop: Iterative sense → infer → act cycle with generative model

Key Files

active_inference.pl — Source implementation
run.sh — Execution script (handles compilation if needed)
README.md — Usage documentation and requirements

Usage

cd 0_CONTEXT/Computer_Languages/Prolog/
./run.sh

Language-Specific Features

Declarative constraint solving
Pattern matching and unification
Backtracking search

Integration

Tested via master_controller.py test prolog
Benchmarked via benchmark_suite.py
Listed in languages.json under category "Logic"

Prerequisites

See README.md for Prolog-specific installation requirements.

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Active Inference in Prolog

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