QuInCA: Quantum-Inspired Cognitive Architecture - v 0.2.0

This project implements a quantum-inspired cognitive architecture using Python. It aims to model complex cognitive processes using quantum-inspired algorithms to investigate the emergence of consciousness or intelligence as a complex system phenomenon.

Features

• Quantum-inspired neural networks
  • Basic version
  • Efficient version
  • Flexible version
  • Enhanced version
  • Unified version (current)
• Modular cognitive architecture including:
  • Perception Module
  • Attention Module
  • Memory Module
  • Reasoning Module
  • Action Selection Module
• Real-time processing framework
• Multi-modal input system (audio, keyboard, mouse, screenshot)
• Extensive printing with logging levels

Requirements

• Python 3.8+
• NumPy
• SciPy
• Pillow (PIL)
• PyAudio
• pynput
• mss

Installation

1. Clone the repository:

   git clone https://github.com/BjornKennethHolmstrom/QuInCA.git
   cd QuInCA
   

2. Create a virtual environment:

   python -m venv quantum_cognitive_env
   source quantum_cognitive_env/bin/activate
   

3. Install the required packages:

   pip install numpy scipy pillow pyaudio pynput mss
   

Usage

Run the main script:

python main.py

Project Structure

• main.py: Entry point of the application
• input_system.py: Handles multi-modal input
• real_time_framework.py: Manages real-time processing
• quantum_inspired_lib/: Contains quantum-inspired neural network implementations
• cognitive_modules/: Contains individual cognitive module implementations

Contributing

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

License

This project is licensed under a custom license, see LICENSE.md