A2C Pendulum is a reinforcement learning agent designed to interact with the Pendulum-v1 environment. The model is associated with deep reinforcement learning techniques and is referenced in connection with stable-baselines3, a well-known reinforcement learning library. Its primary function is to serve as an agent that plays or controls the Pendulum-v1 environment, which is commonly used for testing and benchmarking reinforcement learning algorithms.
The tool can be used with libraries such as stable-baselines3, and instructions are provided for loading the model from the Hugging Face Hub using specific functions. It is also mentioned in the context of usage within notebooks, including platforms like Google Colab and Kaggle, allowing for flexible experimentation and integration into various research or development workflows.
No explicit information is provided regarding the intended audience, licensing, or pricing. The tool is positioned within the class of reinforcement learning agents, specifically for the Pendulum-v1 scenario, and is made available through the Hugging Face platform.
A2C Pendulum sits in PulseGate's Other AI category. It focuses on providing an open-source A2C agent for reinforcement learning research in the Pendulum-v1 environment. It is built as an open-source project for reinforcement learning researchers and developers. A2C Pendulum is open source under the MIT license. It runs on the web and the command line, and it can be self-hosted.
Behind A2C Pendulum is szymon-hyziak, and the product first shipped in 2019. Development happens publicly on GitHub with 13.6k stars and 10 commits in the last 90 days. Key capabilities include reinforcement learning, pendulum-v1 agent, and open weights.
Latest indexed changes and source events
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