I Like Trains

Overview

"I Like Trains" is a multiplayer, real-time, network game where trains controlled by computer programs compete. Programs are written in Python and Pygame is used to render the playing field. Programs score points by collecting and dropping off passengers. The more passengers a train is carrying, the longer and slower it becomes. Programs are therefore expected to implement various strategies while avoiding collisions.

Your objective will be to modify common/agents/agent.py file and implement logic to control your train. You may add additional files to the directory but do not modify any existing files outside of common/agents. You can make different versions of your agent by copying the agent.py file, renaming it and modifying it.

Documentation

For detailed documentation, please refer to the docs directory:

• Setup Instructions - How to set up the project
• Game Modes - Different ways to play the game
• Game Rules - Rules and gameplay mechanics
• Project Structure - Overview of the codebase organization
• Agent Implementation - How to implement your train agent
• Evaluation - Submission requirements
• Configuration - Configuration options and logging
• Version Management - How to update and handle conflicts
• Git Workflow - Using Git for version control

Quick Start

# Clone the repository
git clone https://github.com/vita-epfl/I_like_trains.git
cd I_like_trains

# Install dependencies
pip install -r requirements.txt

Setup your config file

Copy config.json.template to config.json. You can use your graphical interface or one of the following commands:

# Linux/MacOS/Unix
cp config.json.template config.json

# Windows (Command Prompt)
copy config.json.template config.json

# Windows (PowerShell)
Copy-Item -Path config.json.template -Destination config.json

You can leave config.json as-is for now. Later, you will want to adjust the config file if you want to connect to the lab's server or run multiple agents. You will also need to adjust the config if you want to play with the keyboard against your agent.

Setup your agent file

if you don't have any existing agent.py files, copy common/agents/agent.py.template to common/agents/agent.py. You can use your graphical interface or one of the following commands:

# Linux/MacOS/Unix
cp common/agents/agent.py.template common/agents/agent.py

# Windows (Command Prompt)
copy common\agents\agent.py.template common\agents\agent.py

# Windows (PowerShell)
Copy-Item -Path common\agents\agent.py.template -Destination common\agents\agent.py

This will create your agent file that you'll modify to implement your train's behavior. Make sure to update the SCIPERS list in the file with your actual SCIPER numbers.

Run the client

python -m client

For more detailed setup instructions, see the Setup Guide.