name: Active Inference in Tcl description: Tcl implementation of Active Inference with belief updating, free energy minimization, and policy selection
Active Inference in Tcl
Overview
This skill provides a complete Active Inference implementation in Tcl, 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.tcl— Source implementationrun.sh— Execution script (handles compilation if needed)README.md— Usage documentation and requirements
Usage
cd 0_CONTEXT/Computer_Languages/Tcl/
./run.sh
Language-Specific Features
- Rapid prototyping and iteration
- Dynamic typing flexibility
- Rich standard library
Integration
- Tested via
master_controller.py test tcl - Benchmarked via
benchmark_suite.py - Listed in
languages.jsonunder category "Scripting"
Prerequisites
See README.md for Tcl-specific installation requirements.