SCANUE-V - Synthetic Cognitive Augmentation Network Using Experts

🚀 Overview

SCANUE-V (Synthetic Cognitive Augmentation Network Using Experts) advances cognitive augmentation through a biologically inspired modular architecture. Building on the foundation of previous SCAN iterations, SCANUE-V employs a sophisticated system that integrates specialized agent models, adaptive learning, and human-in-the-loop methodologies to improve user alignment and overall cognitive augmentation capabilities.

SCANUE-V draws inspiration from the prefrontal cortex (PFC) and its subregions to simulate core cognitive processes, creating a versatile framework for next-generation cognitive augmentation solutions that can adapt to diverse user needs.

🧠 Biologically-Inspired Architecture

SCANUE-V simulates various subregions of the prefrontal cortex to address intricate cognitive tasks:

• DLPFC (Dorsolateral Prefrontal Cortex): Executive control, working memory, and task planning
• VMPFC (Ventromedial Prefrontal Cortex): Emotional regulation and risk assessment
• OFC (Orbitofrontal Cortex): Reward evaluation and decision-making
• ACC (Anterior Cingulate Cortex): Conflict detection and error monitoring
• MPFC (Medial Prefrontal Cortex): Integration of inputs into value-based recommendations

🔧 Technology Stack

Frontend

• Next.js 15.1.7 with App Router
• React 19 for UI components
• TypeScript for type safety
• Tailwind CSS 4 for styling
• Radix UI for accessible UI components
• Playwright for end-to-end testing

Backend

• FastAPI for high-performance API
• Python 3.13+
• LangGraph for multi-agent state management
• LangChain for multi-agent orchestration
• OpenAI GPT-4o-mini fine-tuned models (one for each PFC-inspired agent)
• PostgreSQL (via asyncpg) for data storage
• JWT for authentication
• Valkey (Redis) for caching

DevOps

• Docker & Docker Compose for containerization
• Traefik for reverse proxy
• GitHub Actions for CI/CD
• CLI Interface for direct system interaction

🔑 Core Features

1. Modular Agent Architecture

SCANUE-V leverages a PFC-inspired modular architecture where specialized agents handle specific cognitive functions, providing more targeted and efficient cognitive augmentation.

2. Information Routing and Processing

• Command line interface for user query submission
• Task delegation and planning by the DLPFC Agent
• Specialized subtask distribution across domain-expert agents
• Parallel processing for improved performance and near real-time responses

3. Human-in-the-Loop (HITL) Integration

• Continuous user feedback integrated into the system's learning process
• Real-time adaptation to user preferences and requirements
• Enhanced ethical alignment and oversight
• Greater contextual understanding compared to traditional reinforcement learning

4. Adaptive Learning

SCANUE-V combines human-in-the-loop methodologies with specialized agent models to continuously improve performance and user alignment.

🚀 Getting Started

Prerequisites

• Docker and Docker Compose
• Node.js 20+ (for local frontend development)
• Python 3.13+ (for local backend development)
• Just command runner (optional, but recommended)

Setup and Installation

1. Clone the repository

   git clone https://github.com/yourusername/SCANUE-V.git
   cd SCANUE-V

2. Environment Configuration

   cp .env.example .env
   # Update .env with your configuration

3. Start with Docker Compose

   docker-compose up -d

   The application will be available at:

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000/docs

Using Just Commands

Just is a handy command runner that simplifies common development tasks. SCANUE-V provides a comprehensive set of Just commands for development workflows:

1. Install Just (if not already installed)

   # On macOS
   brew install just
   
   # On Windows (with Chocolatey)
   choco install just
   
   # On Linux
   apt-get install just

2. View available commands

   just --list

3. Start the entire application stack (primary method)

   just docker-up

4. Start only the frontend

   just frontend

5. Start only the backend

   just backend

6. Run tests

   just test

7. Clean up containers and volumes

   just clean

8. Format and lint code

   just lint

These commands simplify development by providing unified shortcuts across the entire project, regardless of whether you're working on the frontend or backend.

Local Development

Frontend:

cd frontend
npm install
npm run dev

Backend:

cd backend
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -e .
uvicorn app.main:app --reload

📚 Design-Based Research Approach

SCANUE-V's development follows a design-based research (DBR) methodology, informed by:

• IRB-compliant Cognitive Augmentation User Survey Evaluation (CAUSE)
• Technology Acceptance Model (TAM)
• Unified Theory of Acceptance and Use of Technology (UTAUT)
• Jobs-To-Be-Done (JTBD)
• System Usability Scale (SUS)
• NASA Task Load Index (NASA-TLX)

This approach ensures continuous refinement based on user feedback and evolving requirements.

🔮 Future Directions

User Interfaces

Development of graphical user interfaces (GUIs) to enhance workflow visualization, improve multi-agent coordination, and broaden accessibility.

SCANUE Alignment Technique (SCANAQ)

Integration of the SCANAQ instrument, a 36-question tool that focuses on problem-solving and psychological alignment to tailor agent behaviors to user needs.

Advanced Neural Architectures

Exploration of novel neural architectures, such as Spiking Transformer Augmenting Cognition (STAC), and potential noninvasive brain-computer interface integrations.

Ethical and Contextual Adaptations

Refinement of HITL methodologies to reduce bias and address ethical complexities, with applications in healthcare, education, and finance.

🧪 Testing

SCANUE-V employs comprehensive testing strategies to ensure reliability:

Frontend Tests:

cd frontend
npm test

Backend Tests:

cd backend
pytest

End-to-End Testing:

just e2e-test

🛠️ Development Tools

• Just - Command runner (see justfile for available commands)
• Pre-commit - Git hooks for code quality
• ESLint & Ruff - Code linting
• Tailwind CSS - Styling framework
• CLI Testbed - For validating core SCANUE-V functionality

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👏 Acknowledgements

• All contributors who have helped shape SCANUE-V
• The research communities behind prefrontal cortex studies and biologically-inspired AI
• The open-source communities behind Next.js, FastAPI, LangGraph, and all other technologies used in this project