* @param player the player that the AI will identify as * @param board the Tic Tac Toe board to play on * @param maxPly the maximum depth */ The algorithm is simple to implement. -1. After learning the MiniMax algorithm, I decided to practice it on Tic Tac Toe. MiniMax algorithm with alpha beta pruning.

The shortest description of MiniMax that I can find is from Wikipedia. Minimax Algorithm Tic Tac Toe AI In Java [Minimax][Full tree Search][Artificial Intelligence][Java] The minimax tree has leaf values like -1 0 or 1. Min selects the minimum i.e. Prerequisites: Minimax Algorithm in Game Theory, Evaluation Function in Game Theory Let us combine what we have learnt so far about minimax and evaluation function to write a proper Tic-Tac-Toe AI (Artificial Intelligence) that plays a perfect game.This AI will consider all possible scenarios and makes the most optimal move. However, it took me much more time than I expected. This makes the computer unbeatable. Alpha Beta pruning - Minimax Algorithm for Tic Tac Toe [Java]

So, I would like to share what I have learned here. TIC-TAC-TOe. * Uses the MiniMax algorithm to play a move in a game of Tic Tac Toe. */ class MiniMax {private static double maxPly; /** * MiniMax cannot be instantiated. This is a Player vs. Computer game in Java Swing using Minimax Algorithm upto 9 level. This is an Eclipse project built with Java Swing. */ private MiniMax {} /** * Execute the algorithm.

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