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AI Agent for Saboteur Game

Development of an AI agent for the final project of an AI course at McGill

Saboteur is a well known mining-themed board game. This project aims to design an Artificial Intelligence searching algorithm and implement an AI agent for this popular turn-based strategy game. With slightly modified rules, in our Saboteur game, two players will make a move consecutively.

In each move, the corresponding player can either play a card he has in hand on a 15x15 board or discard a card by dropping it. Available Saboteur cards are classified as tile cards which represent the tunnel created and four kinds of functional card: Malus, Bonus, Destroy and Map with different functionalities. The ultimate goal of winning the game is to build a non blocking mining path from beginning position to the actual nugget card position.

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An AI agent for the Saboteur Game

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