Mancala Board Game
Complete Implementation of the Mancala Board Game In Python
This is the second part of a two-part project combining probability simulation and game logic implementation to analyze and build a digital version of the Mancala board game.
The first part explores random number generation and probability convergence to simulate outcomes and model game randomness.
This second part applies these insights to a Python implementation of Mancala, complete with turn logic, scoring, and an optional AI opponent.
In this project, I designed and developed a full implementation of the classic board game Mancala in Python. This project demonstrates the ability to translate real-world game rules into program logic, manage game state, and provide a functional and interactive program.
Key Contributions:
- Implemented core Mancala rules (stone distribution, captures, turn logic, end-game conditions).
- Structured the game using Python functions and data structures for clarity and maintainability.
- Designed logic to handle valid/invalid player moves and enforce rules.
- Tested gameplay across multiple scenarios to ensure correctness.
- Delivered a clean, documented codebase and accompanying report.
Skills Demonstrated:
- Python programming (functions, control flow, state management)
- Game logic design & algorithmic thinking
- Problem decomposition into modular, reusable code
- Testing and debugging interactive systems
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