Build a Tetris Game Using AI: Step-by-Step Guide with Python & Pygame

Difficulty Level: Intermediate

This project involves minimal Python programming skills as well as experience with Pygame-based game development. The AI implementation uses simple heuristics instead of complex machine learning, making it accessible even for beginners with limited experience.

Pre-requisites

Before building the Tetris game using AI, ensure you have the following:

1. Basic Programming Knowledge

Understanding of Python (variables, loops, functions, classes)
Familiarity with basic AI concepts (optional but helpful)

2. Installed Software & Libraries

Python 3.x (Download from python.org)
Install necessary libraries using pip:

bash pip install pygame numpy

3. Development Environment

You can use any code editor or IDE, such as:

VS Code (Recommended)
PyCharm
Jupyter Notebook (for testing AI models)

4. AI Knowledge (Optional but Helpful)

Understanding of heuristics in AI (for optimizing moves)
Basics of Reinforcement Learning (if you want to improve AI decision-making)

Step-by-Step Guide with Python & Pygame

Before starting development, define the core elements of the Tetris game:

Grid Size: A 10×20 board
Tetromino Shapes: 7 different shapes (I, J, L, O, S, T, Z)
Game Mechanics: Piece rotation, collision detection, row clearing
AI Integration: Automatic piece placement using heuristics or machine learning

Step 1: Planning the Game

Before you begin coding, define the core components of your Tetris game:

Grid Size: A 10×20 board
Tetromino Shapes: 7 different shapes (I, J, L, O, S, T, Z)
Game Mechanics: Piece rotation, collision detection, row clearing
AI Integration: Automated piece placement using heuristics or machine learning

Tools & AI Models You Can Use:

Code Generation AI: OpenAI’s Codex, ChatGPT, or Google’s Gemini
Game Design AI: DeepAI, Leonardo.AI, Scenario.gg (for assets)
AI for Optimization: Reinforcement Learning using TensorFlow or PyTorch

Step 2: Setting Up the Development Environment

You’ll need a game development framework and AI tools. In this guide, we’ll use Python and Pygame.

Install Dependencies

First, install Python and the required libraries:

pip install pygame numpy

Step 3: Creating the Game Grid

The Tetris grid is a 10×20 matrix, where each cell represents a block. We initialize it as a 2D list.

Code for the Grid

import pygame
import random

# Define grid size
GRID_WIDTH = 10
GRID_HEIGHT = 20
CELL_SIZE = 30  # Size of each cell

# Initialize the grid (empty = 0)
grid = [[0 for _ in range(GRID_WIDTH)] for _ in range(GRID_HEIGHT)]

Step 4: Defining Tetromino Shapes

Tetris consists of 7 Tetrominoes, each represented as a list of coordinates.

Code for Tetrominoes

TETROMINOES = {
    'I': [[(0, -1), (0, 0), (0, 1), (0, 2)]],
    'O': [[(0, 0), (0, 1), (1, 0), (1, 1)]],
    'T': [[(0, -1), (0, 0), (0, 1), (1, 0)]],
    'S': [[(0, 0), (0, 1), (1, -1), (1, 0)]],
    'Z': [[(0, 0), (0, -1), (1, 0), (1, 1)]],
    'J': [[(0, -1), (0, 0), (0, 1), (1, -1)]],
    'L': [[(0, -1), (0, 0), (0, 1), (1, 1)]],
}

Step 5: Handling Piece Movement

Each Tetromino must:
✅ Move left/right
✅ Move down
✅ Rotate
✅ Detect collision

Code for Movement

class Tetromino:
    def __init__(self, shape, x, y):
        self.shape = shape
        self.cells = TETROMINOES[shape]
        self.x = x
        self.y = y

    def move(self, dx, dy):
        self.x += dx
        self.y += dy

    def rotate(self):
        self.cells = [(-y, x) for x, y in self.cells]  # Rotate 90 degrees

Step 6: Detecting Line Clears

When a row is completely filled, remove it and shift everything above down.

Code for Line Clearing

def clear_lines(grid):
    new_grid = [row for row in grid if any(cell == 0 for cell in row)]
    while len(new_grid) < GRID_HEIGHT:
        new_grid.insert(0, [0] * GRID_WIDTH)
    return new_grid

Step 7: Implementing AI to Play the Game

Now, let’s add AI to automatically play Tetris! The AI will:
✅ Analyze available positions
✅ Choose the best move
✅ Drop the piece accordingly

Step 7.1: Creating a Heuristic Function

A heuristic function evaluates how “good” a board state is. The board is scored based on:

Block Height (lower is better)
Number of Holes (fewer is better)
Lines Cleared (higher is better)

Code for Heuristic Function

def evaluate_board(grid):
    height = sum(row.count(1) for row in grid)
    holes = sum(1 for x in range(GRID_WIDTH) for y in range(GRID_HEIGHT) if grid[y][x] == 0 and y > 0)
    return -height + (10 * holes)

Step 7.2: Implementing AI Decision Making

The AI will simulate all possible moves, evaluate them, and select the best one.

Code for AI Decision Making

def best_move(grid, tetromino):
    best_score = float('-inf')
    best_position = None

    for rotation in range(4):
        for x in range(GRID_WIDTH):
            new_grid = simulate_drop(grid, tetromino, x, rotation)
            score = evaluate_board(new_grid)
            if score > best_score:
                best_score = score
                best_position = (x, rotation)

    return best_position

Step 8: Running the Game

Now, integrate everything into a game loop that:
✅ Spawns new tetrominoes
✅ Moves the current piece
✅ Allows AI to make decisions
✅ Clears lines and updates the screen

Code for the Game Loop

def game_loop():
    running = True
    current_piece = Tetromino(random.choice(list(TETROMINOES.keys())), 5, 0)

    while running:
        best_x, best_rotation = best_move(grid, current_piece)
        current_piece.rotate(best_rotation)
        current_piece.move(best_x, 0)

        # Drop the piece and update grid
        grid = clear_lines(grid)

        # Check for game over
        if any(cell == 1 for cell in grid[0]):
            print("Game Over")
            running = False

Step 9: Adding Graphics

Use Pygame to draw the blocks on the screen.

Code for Drawing the Grid

def draw_grid(screen):
    for y in range(GRID_HEIGHT):
        for x in range(GRID_WIDTH):
            if grid[y][x] == 1:
                pygame.draw.rect(screen, (0, 255, 0), (x * CELL_SIZE, y * CELL_SIZE, CELL_SIZE, CELL_SIZE))

Conclusion

Congratulations! 🎉 You’ve built a Tetris AI that plays the game on its own! 🚀

Ways to Improve:

✔ Add deep learning models for smarter AI
✔ Enhance graphics with animations
✔ Implement multiplayer mode