Ever wondered how artificial intelligence can navigate the complex world of driving? This blog article will guide you through training an AI model to drive a truck in the popular game Euro Truck Simulator 2 (ETS2) using reinforcement learning techniques. Get ready to buckle up!

Understanding the Basics

The goal of this project is to create an AI that can handle steering, accelerating, and braking by utilizing only the buttons W, A, S, and D. Think of it as teaching a child to drive a toy car on a track, making decisions based solely on what they can see and the buttons they can press.

Architecture and Methodology

The AI leverages the reinforcement learning method inspired by the original Atari paper. Imagine it as a child learning to ride a bike. At first, they fall a lot, but gradually they learn how to balance, steer, and pedal correctly. This method involves predicting Q-values that represent future states and rewards based on the child’s actions (or the AI’s button presses).

Key Components of the AI

• Embedder 1: A convolutional neural network (CNN) helps the AI understand the environment.
• Embedder 2: This transforms the output from Embedder 1 into a useful format and includes additional inputs.
• Direct Reward Model: Predicts immediate rewards based on actions and conditions.
• Indirect Reward Model: Forecasts the potential future rewards of different actions.
• Successors: An RNN model that predicts what will happen next based on the current embeddings and chosen actions.

Getting Started with Installation

Ready to dive in? Here’s how you can set up your environment:

Requirements

• Hardware: Nvidia GPU with 8GB+ memory; 32GB+ of RAM.
• Python: Version 2.7 is recommended.
• Libraries: Ensure libraries like imgaug, skimage, PyTorch, and others are installed.

Installation Steps

Follow these steps to install the necessary files:

• Clone the repository: git clone https://github.com/aleju/self-driving-truck.git
• Navigate into the directory and compile the screenshot tool:

cd self-driving-truck/lib
gcc -shared -O3 -Wall -fPIC -lX11 -Wl,-soname,screenshot -o screenshot.so screenshot.c -lX11

• Download the trained models and decompress them as per the project instructions.

Configuring the Game

You’ll need to ensure the Euro Truck Simulator 2 is set up properly:

• Create a new profile with the default truck and easiest gear.
• Adjust settings related to gameplay, graphics, and controls to match specific configurations provided by the project.

Applying the Model

Now you can run the AI in ETS2:

• Start the game while ensuring the settings meet the required conditions.
• Use specific commands like:

cd train_reinforced
python train.py --onlyapply --noinsert --p_explore=0.1

• Keep the game window active and watch as the AI takes over.

Troubleshooting Ideas

As you embark on this journey, challenges may pop up. Here are some tips to manage common issues:

• Game Window Issues: Ensure the game window is fully on screen. If it’s not, reposition it to avoid glitches.
• AI Misbehavior: Tweaking the model settings and training parameters might help enhance performance.
• Slow Performance: Make sure your hardware meets the necessary requirements and the game is running on optimal settings.

For more insights, updates, or to collaborate on AI development projects, stay connected with [fxis.ai](https://fxis.ai).

Final Thoughts

At [fxis.ai](https://fxis.ai), we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

By following this guide, you should be well on your way to developing an impressive self-driving truck AI. Happy driving!