Watch an AI Dominate Tetris on a Real Nintendo!

Watch an AI Dominate Tetris on a Real Nintendo!

Table of Contents

1. Introduction
2. The Challenge of Making an AI for Tetris
3. The Supplies Needed for the Project
4. Creating the Controller Interface
5. Connecting the Arduino to the Nintendo
6. Writing Code for the AI
7. Training the AI in a Tetris Simulation
8. The AI's Performance in the Full Game
9. The Kill Screen Challenge
10. Conclusion

🧩 The Challenge of Making an AI for Tetris

Tetris, a classic game loved by many, poses a unique challenge for AI development. Unlike other AI bots that play pre-planned games on emulators, the aim here is to create an AI that plays Tetris the way humans do. This means it has to rely on the information displayed on the screen and use a physical controller. The real twist? The AI needs to run on a Nintendo Entertainment System from the 80s. Welcome to hard mode!

As the creator of this AI, I have a confession to make - I'm terrible at Tetris. Despite watching others play and growing up with the game, I never quite got the hang of it. But I'm determined to change that by building an AI to conquer Tetris for me. So, let's dive into the process and see how I tackled this challenge.

🧰 The Supplies Needed for the Project

Before we delve into the technical aspects, let's take a look at the supplies required for this ambitious project. Firstly, I opted for a replacement controller instead of an original one to preserve the integrity of the hardware. Next, I acquired an Arduino, a small computer that would help me convert the USB signal from the controller into a voltage, allowing us to hack into the controller itself. Lastly, I obtained a capture device capable of converting the RCA signal from the Nintendo into a USB signal, making it compatible with a computer.

It's worth noting that I opted for a cheaper capture device, although I probably should have invested in a higher quality one. But no worries, we'll work with what we have, and let's hope it doesn't catch fire!

🔌 Creating the Controller Interface

To start building our Tetris AI, we need to create a controller interface that communicates with the Arduino. I took the pins from the buttons on the controller and carefully soldered them to the Arduino's output pins. By manipulating the voltage levels on these pins, we can simulate button presses, fooling the Nintendo into thinking a human is playing. It wasn't the prettiest process, but it was effective.

Now, here's a WORD of caution - I didn't meticulously research the voltage details of the original Nintendo controllers. Instead, I relied on trial and error with a multimeter to determine the appropriate voltages. It's a miracle this whole setup hasn't exploded yet, and I'm half expecting it to burst into flames any moment now. But hey, science is all about taking risks, right?

🔗 Connecting the Arduino to the Nintendo

Now that we have our controller interface ready, the next step is to establish a connection between the Arduino and the Nintendo. By hacking into the controller's signal on its way into the console and capturing the output that would normally go to the TV, we can access the same visual information that a human player would see. This allows our AI to make decisions based on what's happening on the screen.

To achieve this, I utilized the capture device Mentioned earlier, which converts the RCA signal from the Nintendo into a USB signal. It essentially transforms the Nintendo's output into something resembling a USB webcam feed for the computer to receive.

💻 Writing Code for the AI

With our hardware setup complete, it's time to write the code that will bring our Tetris AI to life. But let me warn you - the code for this project is not a sight for sore eyes. It's a tangled mess of spaghetti-like code that's far from elegant. However, it gets the job done.

The critical piece of code I developed analyzes the feed from the capture device, allowing us to identify what's on the screen at any given moment. This visual information is then fed into the AI core, which breaks down the Tetris pieces into active movable ones and fixed background pieces. By considering all possible move combinations and evaluating their potential outcomes, the AI selects the move with the highest likelihood of prolonging survival.

Finally, the chosen move is sent back to the Nintendo through the Arduino as a series of button presses. And just like that, we have an AI player for Tetris!

🎮 Training the AI in a Tetris Simulation

Surprisingly, it turns out that our AI needs some training before it can truly excel at playing Tetris. Realizing that training it in the actual game would be time-consuming, I decided to take a different approach. I created a Tetris simulation that allows me to run multiple instances of the AI simultaneously, significantly speeding up the training process.

So, while we wait for the AI to train, I'll be back in a couple of days to check on its progress. Rest assured, our AI will soon be ready to take on the challenge of the full game!

🏆 The AI's Performance in the Full Game

After patiently waiting and conducting thorough training Sessions in our Tetris simulation, our AI is finally prepared to face the ultimate test - playing the full game. It has surpassed my own skills in every aspect, showcasing its ability to handle the game with precision and finesse.

But now it's time to face the infamous "kill screen." At level 29, the falling Tetris blocks move at such a rapid pace that it becomes nearly impossible to keep up. Even for our AI, this presents a significant challenge. Due to limitations in the capture card's speed and processing capabilities, there is a considerable delay in receiving information, causing the AI to struggle with decision-making during this intense phase.

With time quickly ticking away, the AI desperately evaluates the countless possible moves, rotations, and placements. However, the limited frames and data transmission speed result in failed consistency checks, ultimately leading to the AI's demise. It succumbs to the unforgiving speed of the game, unable to keep up with the lightning-fast pace.

But let's not mourn the AI's defeat. Instead, let's acknowledge the incredible skill demonstrated by human players who have overcome this relentless challenge. Even with off-the-shelf hardware, I have yet to surpass the achievements of these talented individuals. Perhaps investing in a better capture card would have made a difference, but we'll save that for another time.

🎯 Conclusion

In conclusion, creating an AI to conquer Tetris proved to be a thrilling and challenging endeavor. From building the controller interface and connecting the Arduino to the Nintendo, to writing complex code and training the AI, every step was a test of determination and problem-solving skills.

While our AI fell short of conquering the legendary kill screen, it showcased the remarkable abilities of human players who have pushed the boundaries of the game. With future projects on the horizon, such as an AI for Minesweeper that utilizes neural networks, the world of AI gaming continues to evolve.

Thank you for joining me on this journey, and if you enjoyed this video, don't forget to subscribe for more exciting content. Remember, your support through likes and shares can make a genuine difference for small creators like me.

What did you think of our Tetris AI project? Do you have any ideas for other NES games or Tetris-related endeavors? Let us know in the comments below!

Highlights

• Creating an AI to play Tetris on a Nintendo Entertainment System from the 80s is a challenging task.
• The AI needs to rely on on-screen information and use a physical controller.
• The supplies required for the project include a replacement controller, an Arduino, and a capture device.
• By hacking into the controller's signal and capturing the output, the AI can make decisions based on what's happening on the screen.
• The code for the AI is complex and somewhat messy but gets the job done.
• The AI needs training, which is done in a Tetris simulation to speed up the process.
• The AI performs impressively in the full game but struggles with the intense speed of the "kill screen."
• Human players have achieved remarkable feats in Tetris, surpassing what the AI can currently accomplish.
• The project demonstrates the challenges and possibilities of AI in gaming.