> For the complete documentation index, see [llms.txt](https://docs.catanatron.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.catanatron.com/readme.md). # Welcome to Catanatron! Catanatron is a high-performance simulator for The Settlers of Catan, designed to help you develop, test, and benchmark AI players. Whether you're a machine learning researcher, game developer, or just a Catan enthusiast curious about AI strategies, Catanatron provides the tools to explore the full strategic depth of the game at scale. ### What is Catanatron? Catanatron is an open-source project that allows you to: * Run thousands of Catan games per minute between different bots. * Develop your own AI players with simple Python interfaces. * Test strategies using weighted decision trees or custom algorithms. * Train reinforcement learning agents using an OpenAI Gym-compatible environment. * Web UI to watch, inspect, and play games against Catanatron! ### Getting Started You can start simple by playing against catanatron at [https://www.catanatron.com](https://www.catanatron.com/). Or jump right in:
Getting StartedRunning a simulationScreenshot 2025-05-21 103849.pngQuickstart
Simulation HooksLearn how to compute statistics on simulationsScreenshot 2025-05-21 104023.pnghttps://github.com/bcollazo/catanatron/blob/master/documentation/broken-reference/README.md
Graphical User InterfaceImprove the web UICatanatronUI.pnghttps://github.com/bcollazo/catanatron/blob/master/documentation/broken-reference/README.md
--- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.catanatron.com/readme.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `build a script that syncs our docs to a CMS` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.