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# 100 Prisoners Simulator
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A Python simulation of the **100 prisoners problem**, where each prisoner must find their own number hidden in one of 100 boxes.
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This project allows you to run multiple simulations using **custom strategies**, view success rates, and manage runs through a clean working directory system.
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This project allows you to run multiple simulations using **custom strategies**, view success rates, and manage runs through a clean **simulation ID** system.
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If you have any questions or suggestions, feel free to open an issue or submit a pull request! It would make my day. 😊
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- Overall chance of success
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- Average number of checked boxes per prisoner
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- Percentage of finds per prisoner
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- Built-in directory management for saving results and configurations
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- Built-in simulation management using IDs for saving and loading configuration and progress
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## 🧠 About the Project
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I created this simulator because I wanted a way to **easily prove the math** behind the 100 prisoners problem, and to **experiment with different strategies** that people have come up with, maybe even stumble upon a new, better one. 😉
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I created this simulator because I wanted a way to **easily prove the math** behind the 100 prisoners problem, and to **experiment with different strategies** that people come up with, maybe even stumble upon a new, better one. 😉
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The 100 prisoners problem is a classic probability and logic puzzle. Each prisoner may open up to half the boxes (50) to find their number.
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If **all** prisoners succeed, they are freed; if even one fails, they all lose.
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## ⚙️ Usage
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1. Download the [latest release](https://github.com/TechRedByte/Prisoners-Riddle/releases/latest)
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2. Unzip the downloaded .zip file
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3. Create a working directory in the root folder (e.g., "Prisoners-Riddle/experiments/test1")
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4. Copy the config.py file to your working directory and configure your strategy and other parameters inside the config file
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5. Run the main Python file:
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3. Customize the simulation settings and the strategy in config.py
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4. Run the main Python file:
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```bash
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python main.py
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```
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## 🧩 Future Ideas
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- Better GUI
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- Seed customizability
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- Parallelized simulations for faster results

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