Tic-Tac-Toe Game in Python - Unbeatable Minimax AI

The video begins with an introduction to creating a Tic Tac Toe game featuring an unbeatable AI using Pygame in Python. The host presents a motivational preview, showcasing the final result of the game, which includes a 3x3 grid where players can make moves by clicking on the screen. The AI, which the host claims is unbeatable, plays perfectly according to the rules of Tic Tac Toe, ensuring it can only end in a tie unless the player makes a mistake. The video is aimed at both beginners and intermediate programmers who will learn to work with Pygame and implement the Minimax AI algorithm.

The host proceeds to guide viewers on setting up the necessary packages for the game, which include Pygame and Numpy. They instruct viewers to open their command line and install these packages using pip or pip3. Additionally, they mention the need to import the 'sys' module for the exit function to terminate the application and to import Pygame and Numpy. The host then outlines the first steps in coding, which involve initializing Pygame and defining constants for the game's geometry, such as sizes, colors, and proportions.

The video script details the process of defining various constants and colors that will be used throughout the game's code. These include RGB values for white, gray, red, green, and black colors, which correspond to different game states like default, tie, win, lose, and background, respectively. The host also defines the window size, line width for the grid, and the size of the squares on the game board, as well as the radius and line width for the player icons (circles and crosses).

The host explains how to initialize the game screen using Pygame, setting the screen size to 300x300 pixels and filling it with a black color. They then define the game board as a 3x3 Numpy array filled with zeros, representing empty fields. The script also includes a function to draw the grid lines on the screen, which can change color depending on the game's outcome, such as green for win, red for loss, and gray for a tie.

The script describes functions for drawing game figures on the board, such as circles and crosses, depending on whether it's the player's or AI's turn. It includes a function to mark a square on the board for a specific player and checks if a square is available for marking. Additionally, there are functions to check if the board is full and to determine if there's a win, considering rows, columns, and diagonals for three-in-a-row victories.

The host delves into the core of the AI's intelligence by implementing the Minimax algorithm. This recursive function evaluates the board state and simulates all possible moves and countermoves to determine the best course of action for the AI. The Minimax function considers win, loss, and tie scenarios, assigning scores to each to guide the AI's decision-making process. The explanation covers the base cases for the recursion and the strategy behind choosing the move that maximizes the AI's chances of winning while minimizing the player's.

The script outlines a function to determine the best move for the AI using the Minimax algorithm. It initializes with a default move and score, then iterates over the board to find the move that yields the highest score, considering the AI's perspective. The function evaluates each possible move, simulates the opponent's response, and selects the move that results in the best outcome for the AI. The process involves recursive calls to the Minimax function until a base case is reached.

The host introduces a function to restart the game, which resets the board and redraws the grid lines. The script then describes the main game loop, which handles events like mouse clicks and key presses to play the game. The loop includes logic for changing players, checking for wins, and handling game over conditions. It also incorporates the AI's turn, using the previously defined function to make the best move. The loop continues, updating the game state and redrawing the figures until the game is over, at which point it checks for a win, loss, or tie.

In the final part of the script, the host engages in a debugging session, identifying and fixing issues in the code that prevent the game from running correctly. They make adjustments to the 'is board full' and 'check win' functions and ensure that the AI's moves are displayed correctly. After resolving the issues, the host demonstrates the game, highlighting the AI's unbeatable strategy. They conclude the video by inviting viewers to like, comment, and subscribe for more content, and thank them for watching.