In this project, we get familiar with the concept of Adversarial Search, Game theory, and how to work with multi-agent environments. I implemented the minimax algorithm and got deeper into the concept of adversarial search.
Checkers is a classic board game played on an 8x8 grid, with each player initially having 12 pieces. The pieces move diagonally forward and can capture opponent pieces by jumping over them. The objective is to either capture all opponent's pieces or block them from moving.
The Minimax Algorithm is a recursive or backtracking algorithm used in decision-making and game theory. It aids in determining the optimal move for a player by assuming that the opponent is also playing optimally. This makes it particularly useful in games like Checkers, where each player aims to maximize their advantage while minimizing their opponent's advantage.
For further details, refer to Mini-Max Algorithm.
The primary objective of this project is to implement the Minimax Algorithm and utilize it to play the game of Checkers effectively. By doing so, we aim to demonstrate the strategic decision-making capability of this algorithm in the context of Checkers, highlighting its role in creating an intelligent player.