{"repo":"Unity-Technologies/ml-agents","free":true,"listed":false,"github":"https://github.com/Unity-Technologies/ml-agents","clone":"git clone https://github.com/Unity-Technologies/ml-agents.git","description":"The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.","language":"C#","stars":19630,"topics":["reinforcement-learning","unity3d","deep-learning","unity","deep-reinforcement-learning","neural-networks","machine-learning"],"license":null,"category":"machine-learning","readme_excerpt":"Unity ML-Agents Toolkit (latest release) (all releases) The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents. We provide implementations (based on PyTorch) of state-of-the-art algorithms to enable game developers and hobbyists to easily train intelligent agents for 2D, 3D and VR/AR games. Researchers can also use the provided simple-to-use Python API to train Agents using reinforcement learning, imitation learning, neuroevolution, or any other methods. These trained agents can be used for multiple purposes, including controlling NPC behavior (in a variety of settings such as multi-agent and adversarial), automated testing of game builds and evaluating different game design decisions pre-release. The ML-Agents Toolkit is mutually beneficial for both game developers and AI researchers as it provides a central platform where advances in AI can be evaluated on Unity’s rich environments and then made accessible to the wider research and game developer communities. Features - 17+ example Unity environments - Support for multiple environment configurations and training scenarios - Flexible Unity SDK that can be integrated into your game or custom Unity scene - Support for training single-agent, multi-agent cooperative, and multi-agent competitive scenarios via several Deep Reinforcement Learning algorithms (PPO, SAC, MA-POCA, self-play). - Support for learning from ","default_branch":null,"files":null,"tree":[],"storefront":"/r/Unity-Technologies","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Unity-Technologies/ml-agents/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}