AI Mancala Agent – Game Theory & Minimax Strategy | Final Project Showcase
Автор: נועה אברמוביץ
Загружено: 2025-07-19
Просмотров: 13
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🎮 Welcome to our AI Mancala Project!
In this video, we showcase our final project for the Advanced Algorithms course.
We developed an intelligent Mancala-playing agent using classic and advanced search strategies such as Minimax and Iterative Deepening.
Our agent evaluates game states using two custom evaluation functions:
A basic utility function based on score differences
An advanced function that considers steal opportunities, blocking, penalties, extra turns, and more!
🎯 Technologies used:
Language: Python
GUI: Custom interface with intuitive visuals
🧠 Main Highlights:
Smart decision-making in dynamic environments
Forced-capture and blocking rules implemented
Visualization of game logic and outcomes
✨ We learned how to turn game theory into a functional, strategic system.
Enjoy watching the demo and feel free to leave a comment or question below!
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