ClueChain: A Bayesian Network-Based Mystery Solver Application

Overview

ClueChain is a mystery solver application that uses Bayesian networks to solve fictional mystery scenarios. The application allows users to input various clues and evidence related to a crime and then applies Bayesian inference to calculate the probabilities of different suspects being guilty. The system provides an interactive and data-driven way to deduce the most likely suspect based on the provided evidence.

Features

• Clue Input: Users can provide various clues or pieces of evidence that may relate to the crime.
• Bayesian Inference: The system applies Bayesian networks to calculate the likelihood of suspects being guilty based on inputted clues.
• Interactive UI: The application provides an easy-to-use interface for adding clues, viewing results, and understanding the logic behind the probability calculations.
• Mystery Scenarios: The app can be used for various fictional mystery scenarios, making it adaptable to a variety of situations.

Usage

To run the project, execute the main.py file:

python main.py

You will be prompted to enter clues and evidence for the mystery, and the application will use Bayesian inference to calculate and display the probability of different suspects.

Project Structure

The repository is organized as follows:

ClueChain/
│
├── main.py                  # Main code file to run the project
├── README.md                # Project documentation (this file)
├── requirements.txt         # List of libraries and dependencies
│
├── data/                    # Subfolder containing datasets
│   └── sample_data.json     # Example dataset used for testing
│
├── support/__pycache__      # Subfolder containing other code files
│   ├── __init__.py          # Code for Bayesian network logic
│   ├── mystery_solver.py    # Code to handle clue input from the user
│
└── others/                      # Subfolder for project-related documents
    ├── final_presentation.pptx  # Final presentation file
    ├── final_report.pdf         # Final project report
    ├── update_presentation.pptx # Updated presentation file
    ├── update_report.pdf        # Updated project report
    └── demo_video.mp4           # One-minute demo video of the project

App Demo Video

• https://drive.google.com/file/d/1K8eWZnUt700NAgQ1YDsMNBYJ5NNY8z62/view?usp=sharing

Requirements

This project relies on the following technologies:

• numpy - For numerical calculations
• pgmpy - For creating and manipulating Bayesian networks
• streamlit Web application interface
• Graphviz - Visualization of network structures
• matplotlib - For visualizing the Bayesian network and results
• json - For handling input and output in JSON format
• Python 3.8+

To install all the necessary dependencies, simply run:

pip install -r requirements.txt

Contributing

We welcome contributions to enhance the ClueChain project. If you would like to contribute, follow these steps:

1. Fork this repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your changes to your forked repository.
5. Open a pull request to merge your changes into the main repository.

License

This project is licensed under the MIT License. See the LICENSE file for more information.

Acknowledgments

• Thanks to all contributors and open-source libraries that helped in the development of ClueChain.
• Special thanks to Dr. Mohammad Shifat-E-Rabbi (MSRb).