🔮 Champion Gen42 - Glass Box Quine Brain

THIS IS THE OPPOSITE OF A BLACK BOX
Every weight, decision, and mutation is fully transparent.

▶️ Try It Live

🌌 CASCADE Hyperlattice Demo — Real-time 3D visualization with HOLD protocol

What Is This?

A self-contained, merkle-hashed AI agent that can:

Run inference with full transparency
Verify its own integrity via quine hash
Be replicated without external dependencies
Log every decision to a provenance chain

Architecture

TIER 1 - RSSM (Recurrent State Space Model)
  • DreamerV3 L-size: deter=4096, stoch=32x32
  • Total latent: 5120 dimensions
  
TIER 2 - LoRA Adapter (EVOLVED)
  • ~82K parameters, rank=16
  • Maps latent → 8 action logits
  
TIER 3 - Evolved Traits
  • Hyperparameters discovered via NEAT-style evolution

Quine Properties

Property	Value
Merkle Hash	`38438eb04586975cda66a08fd3c447bb`
Generation	42
Fitness	0.5879
Brain Type	DreamerV3

Quick Start

# Load from Hugging Face
from huggingface_hub import hf_hub_download
import importlib.util

# Download the self-compiling champion
path = hf_hub_download(
    repo_id="tostido/Champion-Dreamer",
    filename="champion_gen42.py"
)

spec = importlib.util.spec_from_file_location("champion", path)
champion = importlib.util.module_from_spec(spec)
spec.loader.exec_module(champion)

# Create agent
agent = champion.ChampionAgent()

# Verify integrity
assert agent.verify_quine_integrity()

# Run inference
obs = [0.0] * 64  # Your observation
action_probs, value = agent.forward(obs)
print(f"Action: {action_probs.argmax()}, Value: {value:.4f}")

# Full transparency
agent.show_readme()

Export to ONNX/PyTorch

# The champion can compile itself to standard formats
agent.export_onnx("champion.onnx")
agent.export_pytorch("champion.pt")

🛑 HOLD Protocol

Human-in-the-loop oversight at inference time:

# Run with HOLD (requires cascade-lattice)
result = agent.forward_hold(obs, blocking=True, timeout=30.0)

# Result includes:
# - action: final action taken
# - was_override: True if human intervened
# - hold_id: merkle hash of decision point

💼 Quine Brain Conversion Service

Want your model wrapped as a Glass Box Quine Brain?

I offer conversion services for:

Custom RL agents
Foundation models
Any PyTorch/JAX model

What you get:

✅ Self-contained single-file capsule
✅ Merkle-hashed provenance
✅ Quine verification (tamper-proof)
✅ HOLD protocol integration
✅ Full transparency APIs

📧 Contact: [towers.jeff@gmail.com]

Files

File	Description
`champion_gen42.py`	The complete quine brain (~481MB with embedded weights)
`requirements.txt`	Dependencies for running locally

Related Resources

🌌 CASCADE Hyperlattice Demo — Live 3D visualization
📊 Observations Dataset — Every inference logged
📦 Training Data — Evolution logs, fitness traces
🐍 cascade-lattice — Provenance tracking library

License

MIT — Use freely, but the quine hash proves provenance.

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Reinforcement Learning

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