Predictive Coding Implementation

Overview

This project implements predictive coding models in Python, focusing on virtual human experiences. It includes both standalone implementations and a Kafka-integrated version for real-time processing.

Project Structure

.
├── predictive_coding/
│   ├── 01_predcod.py         # Basic predictive coding implementation
│   ├── 02_predcod_nova.py    # Enhanced Nova implementation
│   ├── 03_kafka_nova_poc.py  # Kafka-integrated version
│   └── utils/
├── docs/                 
├── requirements.txt
├── pyproject.toml      
└── setup.py

Technical Stack

• Python-based implementation
• Core dependencies:
  • NumPy: Numerical computing
  • Matplotlib: Data visualization
  • confluent-kafka: Kafka client for real-time processing
  • python-dotenv: Environment variable management

Development Setup

1. Create a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

2. Install dependencies:

   pip install -r requirements.txt

3. Environment Configuration:

   • For Kafka integration, set up appropriate environment variables
   • Use .env file for local development

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests
5. Submit a pull request

License

This project is licensed under the MIT License.

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Part of the Virtual Humans research at Fontys ICT, Lectorate IxD.