Kessler is a simulation environment loosely modeled after our internal project PsiBee and the external project Fuzzy Asteroids. The game has ships that shoot bullets at asteroids to gain score. Ships can collide with asteroids and lose lives. If the ship runs out of lives, the game terminates. In multi-ship scenarios, ships can collide with each other as well, but cannot shoot each other.
Kessler can be built as python extension for install using pip, or used as a local package by copying the
src/kessler_game directory to your project. Wheels are provided in
releases for install using:
pip install <path to kessler_game-#.#.#-py3-none-any.whl>
Kessler has two primary graphics modules. The first uses Python's Tkinter UI library to display the game. The second utilizes a separate executable process called kessler_graphics made in Unreal Engine 5. Data is sent to the kessler_graphics instance using UDP protocol on a local machine.
Under kessler_graphics is an Unreal Engine 5 project for receiving simulation data from the Kessler Python process and displaying it in a 3d environment. To contribute to the UE5 project, you will need to do the following.
kessler_graphics.uproject under the kessler_graphics directory and select "Generate Visual Studio Project Files" from the context menukessler_graphics.uproject, and select "Yes" if prompted to rebuild engine modulesDocumentation is not yet available for Kessler. If you would like to contribute to documentation, check out CONTRIBUTING.md for info on how to get started
If you are interested in contributing to the Kessler project, start by reading the Contributing guide.
Kessler is licensed under the Apache 2.0 license. Please read LICENSE for more information.
FAQs
Asteroids game simulation environment for ML and AI applications
We found that KesslerGame demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
CAI is a new open source AI framework that automates penetration testing tasks like scanning and exploitation up to 3,600× faster than humans.
Security News
Deno 2.4 brings back bundling, improves dependency updates and telemetry, and makes the runtime more practical for real-world JavaScript projects.
Security News
CVEForecast.org uses machine learning to project a record-breaking surge in vulnerability disclosures in 2025.