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🌌 ReasonForge

The Decentralized Marketplace for Verifiable Intelligence

A Bittensor Subnet Proposal | Subnet Ideathon Round I

License: MIT Python 3.9+ React FastAPI

Live DashboardTechnical DocumentationGitHub Source


📖 Overview

ReasonForge is a next-generation Bittensor subnet designed to incentivize structured, auditable reasoning chains. While existing AI subnets often prioritize raw generation speed or generic quality, ReasonForge focuses on the integrity of the thought process.

By leveraging a mathematically rigorous protocol, ReasonForge transforms raw compute into Verifiable Intelligence. Whether it's complex logical proofs, causal inference, or high-stakes financial modeling, ReasonForge ensure that every answer is backed by a transparent, verifiable chain of logic.

🎯 Key Pillars

  • Verifiable Chains: Every response includes an auditable reasoning path.
  • Mathematical Rigor: 13 unique formulas governing every aspect of the network.
  • Validator Accountability: Quadratic slashing and reputation-weighted rewards.
  • Trap Detection: Integrated mechanisms to catch lazy or malicious actors.

🛠️ Quick Start

Experience the power of the ReasonForge protocol locally in minutes.

1. 🧬 Simulation Environment

Clone the repository and install the core protocol package:

pip install -e .
python -m reasonforge.run --epochs 10 --emission 100 --output results.json --seed 42

2. ⚡ Developer API

Spin up the FastAPI server to interface with the simulation engine:

pip install fastapi uvicorn
uvicorn api.server:app --reload --port 8000

3. 🎨 Interactive Dashboard

Launch the high-fidelity visualization suite:

npm install
npm run dev

🏗️ System Architecture

ReasonForge is built on a modular "Separation of Concerns" architecture, ensuring scalability and ease of integration.

Component Tech Stack Responsibility
Core Engine Python Implementation of all 13 whitepaper formulas.
Epoch Simulator Python Full-cycle network simulation (Miners/Validators).
Interactive UI React/TS Real-time visualization of network health and rewards.
Plagiarism Guard Python Jaccard-based similarity detection for network integrity.
Validation Layer Pytest Comprehensive suite of 60+ tests for formula accuracy.

📐 The Mathematical Core

ReasonForge is governed by 13 core formulas that ensure game-theoretic stability and fairness.

💎 Composite Miner Score (CMS)

$$CMS = 0.40Q + 0.30A + 0.15N + 0.15Eff$$

  • Q: Path Quality
  • A: Accuracy
  • N: Novelty
  • Eff: Efficiency

⚖️ Validator Accuracy (VAS)

$$VAS = 1 - \text{mean}(|v_{\text{score}} - \text{consensus}|)$$

🛡️ Quadratic Slashing

$$Slash = 0.05 \times \text{Stake} \times (0.60 - VAS_{7d})^2$$


👥 Network Profiles

⛏️ Simulated Miners

We simulate a diverse range of 12 miners to test protocol resilience:

  • Elite (m-001, m-002): High-performance reasoning nodes.
  • Adversarial (m-011, m-012): Testing plagiarism and spam detection.

🛡️ Simulated Validators

6 distinct validator archetypes:

  • Honest (v-001, v-002): High stake, high accuracy.
  • Lazy/Malicious (v-005, v-006): Triggering slashing and penalty mechanisms.

🛣️ Roadmap

  • Phase 1: Core Mathematical Engine & 13 Formulas.
  • Phase 2: Multi-Epoch Simulator & CLI.
  • Phase 3: FastAPI Integration & SSE Streaming.
  • [wip] Phase 4: Mainchain Integration & Bittensor Onboarding.

📜 License & Acknowledgments

This project is licensed under the MIT License.

Developed with ❤️ by RAVI SHANKAR BEJINI Empowering the world with Verifiable Intelligence

Contact | LinkedIn | Twitter

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The decentralized marketplace for verifiable intelligence for AI

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