| name | Active Inference in COBOL |
| description | COBOL implementation of Active Inference with belief updating, free energy minimization, and policy selection |
Active Inference in COBOL
Overview
This skill provides a complete Active Inference implementation in COBOL,
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.cob — Source implementation
run.sh — Execution script (handles compilation if needed)
README.md — Usage documentation and requirements
Usage
cd 0_CONTEXT/Computer_Languages/COBOL/
./run.sh
Language-Specific Features
- Enterprise heritage and reliability
- Structured data processing
- Fixed-point arithmetic precision
Integration
- Tested via
master_controller.py test cobol
- Benchmarked via
benchmark_suite.py
- Listed in
languages.json under category "Legacy"
Prerequisites
See README.md for COBOL-specific installation requirements.