Factorio-Learning-Environment
Visit Toolfactorio-learning-environment is an AI Agents & Automation tool that provides an open-ended environment for evaluating LLMs in Factorio. It's an open-source framework for developing and testing AI agents.
factorio-learning-environment is an AI Agents & Automation tool that provides an open-ended environment for evaluating LLMs in Factorio. It's an open-source framework for developing and testing AI agents.
About
factorio-learning-environment is an open-source framework designed for developing and evaluating Large Language Model (LLM) agents within the game Factorio. It offers a non-saturating, open-ended environment, making it ideal for assessing the capabilities of LLMs in complex, dynamic settings. The framework supports agent interaction through a Read-Eval-Print-Loop (REPL) pattern, where agents observe the world via output streams, generate Python programs for actions, and receive feedback from the environment. This setup facilitates the development of agents capable of sophisticated problem-solving and decision-making. The project encourages contributions from the AI research community, particularly those interested in building robust evaluation environments for post-AGI frontier models. It includes quick installation guides for Docker and Python, along with optional features for evaluation, MCP protocol support, and PostgreSQL integration.