---
title: Minimal Self Awareness
emoji: 👁
colorFrom: red
colorTo: blue
sdk: gradio
sdk_version: 6.0.1
app_file: app.py
pinned: false
license: other
short_description: 'this space  documents the 3 minimum requirements 4awareness '
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/685edcb04796127b024b4805/WD3U3Qw3UGb5KmytR3yS5.png
---
# Minimal Self in a 3×3 World — RFT Cognitive Core

This Space runs the full implementation of the Rendered Frame Theory (RFT) Minimal Self: a 3×3 embodied agent that learns to predict, explore, and socially mimic using transparent Q-learning and observer-anchored simulation.

## Features
- Agent state: `[x, y, body_bit]` with optional obstacle and social entity
- Counterfactual prediction loop: “If I do this, where will I be?”
- Q-learning with ε-greedy exploration and reward shaping
- Metrics: predictive rate, coherence (`C_min`), body bit strength, and toy integrated information (`Φ_min`)
- Optional moving obstacle and social mimicry
- Live plots and downloadable `results.csv`

## How to Use
1. Choose number of steps, learning rate, and reward type.
2. Toggle obstacle or social entity.
3. Click **Run simulation** to generate metrics and path plots.
4. Download results as CSV for further analysis.

## Experiments
This agent supports 7 experimental modes:
- Passive centering
- Obstacle avoidance
- Explore & Grow
- Social mimicry
- Full social cognition

## Citation
Grinstead, L. (2025). *Minimal Self in a 3×3 World: RFT Cognitive Core*.  
Independent Researcher, Infinite Codex Project.

## License
This Space is governed by a custom Codex license. All reuse requires explicit permission and citation.  
See `LICENSE` file for details.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference