Coding an UNBEATABLE Tic Tac Toe AI (Game Theory Minimax Algorithm EXPLAINED)
TLDRThis video tutorial demonstrates how to create an unbeatable Tic Tac Toe AI using the minimax algorithm, a decision-making process used in game theory. The script explains the concept of game states, utility functions, and how to implement the minimax algorithm to ensure the AI always makes the best move. The video also covers the coding of different player types, including a smart AI player, and concludes with a demonstration of the AI playing against itself and a human, showcasing its unbeatable strategy.
Takeaways
- 😲 The video demonstrates coding an unbeatable Tic Tac Toe AI using the minimax algorithm.
- 🎲 The Tic Tac Toe board has nine squares and can generate approximately 20,000 unique game states.
- 🧠 The minimax algorithm is used to determine the best move by simulating all possible game outcomes.
- 🔢 A utility function is introduced to assign a value to each game state, helping to decide optimal moves.
- 🏆 The AI is programmed to maximize its own wins while minimizing the opponent's chances of winning.
- 💡 The script explains how to implement a recursive minimax function to find the best move in a game tree.
- 👾 The video includes a demonstration of the AI playing against a random player and another AI to test its effectiveness.
- 📝 The implementation details of the Tic Tac Toe game, including board initialization and move validation, are covered.
- 🤖 Different player types are created: human, random computer, and smart computer using the minimax algorithm.
- 🔄 The minimax function is explained with a focus on how it handles game states and propagates utility values back up the game tree.
- 🌐 The final game setup allows for various player combinations, enabling human vs. AI or AI vs. AI gameplay.
Q & A
What is the minimax algorithm and how is it used in Tic Tac Toe?
-The minimax algorithm is a decision-making algorithm used in game theory, particularly for two-player, zero-sum games like Tic Tac Toe. It's designed to minimize the maximum possible loss, or maximize the minimum possible gain. In Tic Tac Toe, it's used by the AI to simulate all possible moves and outcomes to determine the best move that will either lead to a win or prevent a loss.
How many total possible states are there in a game of Tic Tac Toe?
-There are approximately 20,000 possible states in a game of Tic Tac Toe, calculated by raising 3 to the power of 9 (3^9), considering each square on the board can be empty, have an 'X', or have an 'O'.
What is a utility function in the context of the minimax algorithm?
-A utility function is a scoring system used in the minimax algorithm to evaluate the desirability of different game states. It assigns a numerical value to each possible outcome, with positive values for wins, negative for losses, and zero for draws, allowing the algorithm to choose the optimal move.
How does the AI determine the best move in Tic Tac Toe using the minimax algorithm?
-The AI determines the best move by exploring all possible moves from the current game state, evaluating each using the utility function, and choosing the move that maximizes its own utility (i.e., leads to a win or minimizes loss) while assuming the opponent will play optimally.
What is the role of the 'Maximizer' and 'Minimizer' in the minimax algorithm?
-In the minimax algorithm, the 'Maximizer' is the player trying to maximize their own score, while the 'Minimizer' is the opponent trying to minimize the Maximizer's score. The algorithm alternates between these two roles as it explores the game tree to find the optimal move.
How does the AI handle a tie in Tic Tac Toe?
-In Tic Tac Toe, if the board is full and neither player has won, the game is a tie. The AI handles this by assigning a utility value of zero to such a state, indicating neither a win nor a loss, and it will aim to avoid moves that lead to a tie if a winning move is available.
What is the significance of the number of remaining squares in the utility function?
-The number of remaining squares is significant in the utility function because it helps to prioritize moves that lead to a win sooner rather than later. A win achieved with fewer moves is considered more valuable, so the utility function often includes a factor that increases with the number of remaining squares.
How does the AI handle the first move in a game of Tic Tac Toe?
-For the first move in Tic Tac Toe, the AI can either choose a random move or follow a heuristic that suggests certain moves are slightly more advantageous, such as the center square. However, since the game is symmetric at the start, any move is theoretically optimal in the first turn.
What are the different types of players implemented in the Tic Tac Toe AI?
-The Tic Tac Toe AI implementation includes different types of players: a Human player, a Random Computer player, and a Smart Computer player. The Human player takes user input for moves, the Random Computer player chooses moves randomly, and the Smart Computer player uses the minimax algorithm to make optimal moves.
How does the AI know when the game has been won?
-The AI checks for a win by looking for three consecutive 'X's or 'O's in any row, column, or diagonal after each move. If such a sequence is found, the current player is declared the winner, and the game ends.
Outlines
🎮 Tic-Tac-Toe AI Algorithm
The speaker shares their experience coding a Tic-Tac-Toe game and developing an AI that can't be defeated. They explain the game's mechanics, the finite number of possible states, and how the minimax algorithm is used to teach the computer to play optimally. The minimax algorithm is described as a decision-making process involving a Maximizer and a Minimizer, aiming to maximize wins while minimizing losses. A utility function is introduced as a measure of the value of the game's outcome. The speaker provides an example of how the minimax algorithm is applied in a partially completed game of Tic-Tac-Toe, detailing the process of evaluating each move and propagating utility values to determine the best path to victory.
💻 Implementation of Tic-Tac-Toe
The speaker discusses the implementation of the Tic-Tac-Toe game, including the creation of a class for the game board and functions for printing the board, making moves, and checking for a winner. They explain how the game board is initialized and how moves are made, including checks for valid moves and winner determination. The speaker also introduces a superclass called 'Player' and subclasses for different types of players, including human, random computer, and smart computer players. The smart computer player utilizes the minimax algorithm to make optimal moves. The minimax function is described in detail, including its recursive nature and how it evaluates the best move by considering all possible game outcomes.
👾 Playing the Game with Different Players
The speaker concludes by discussing how to play the Tic-Tac-Toe game with different types of players, including humans and various AI players. They explain how to set up the game with different player configurations and how the game progresses, alternating between players until the board is full or a winner is declared. The speaker also mentions the option to print the game's progress for visual tracking. The video ends with a demonstration of playing a game and the outcome, highlighting the effectiveness of the smart AI player.
Mindmap
Keywords
💡Tic Tac Toe
💡Minimax Algorithm
💡Maximizer and Minimizer
💡Utility Function
💡Game State
💡Recursive Algorithm
💡Backtracking
💡Optimal Move
💡Human Player
💡Random Computer Player
💡Smart Computer Player
Highlights
Coding a Tic Tac Toe AI that can't be defeated using the minimax algorithm.
Creating a weak player to test the AI against, ensuring the smart AI never loses.
Exploring the total number of possible game states in Tic Tac Toe.
Understanding that Tic Tac Toe has a finite number of states, making it ideal for the minimax algorithm.
The minimax algorithm is based on the concept of a Maximizer and a Minimizer.
Using a utility function to measure the value of the final result in the game tree.
Maximizing the win for X and minimizing the loss for O in the utility function.
Mapping out all possible scenarios of gameplay to find the most optimal path.
Propagating utility values back up the game tree to find the best move.
Implementing a Tic Tac Toe class with a board and current winner.
Defining a function to check for a winner after each move.
Creating interchangeable player types: human, random computer, and smart computer.
The smart computer player uses minimax for optimal move selection.
The minimax function checks if the previous move was a winner and returns the utility of it.
Setting up the game to play with different player combinations.
Playing a game and visually tracking the moves and outcomes.
