ppo-LunarLander-v2 is an open-source reinforcement learning model trained with PPO for the LunarLander-v2 environment. It enables researchers to evaluate and experiment with RL agents in simulated environments.
In the Other AI space, Ppo LunarLander takes a focused approach. It focuses on providing a pre-trained PPO reinforcement learning agent for the LunarLander-v2 environment. It is built as an open-source project for AI researchers and reinforcement learning practitioners. Ppo LunarLander is open source under the MIT license. Ppo LunarLander is available on the web and the command line, and it can be self-hosted.
Behind Ppo LunarLander is ldihel, and the product first shipped in 2019. Development happens publicly on GitHub with 13.6k stars and 10 commits in the last 90 days. The category is crowded — PulseGate's index counts 21 comparable apps. Key capabilities include reinforcement learning, game agent, and stable-baselines3 compatible.
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ldihel/ppo-LunarLander-v2 discovered by the PulseGate indexer
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