Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
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Updated
Jul 24, 2021 - Python
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Proximal Policy Optimization (PPO) algorithm for Contra
This is a reinforcement learning algorithm library. The code takes into account both performance and simplicity, with little dependence.
PPO, DDPG, SAC implementation on mujoco environment
Proximal Policy Optimization with Tensorflow 2.0
Proximal Policy Optimization (PPO) algorithm for Sonic the Hedgehog
World Models Experiments for Duckietown
Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
OpenAI's PPO baseline applied to the classic game of Snake
Generative Adversarial Model that generates parse trees
World Models Experiments for Duckietown
Proximal Policy Optimization using Pytorch and the Unity Reacher environment.
Clean and flexible implementation of PPO (built on top of stable-baselines3)
Experiments with multiple reinforcement ML algorithms to learn how to beat Street Fighter II
Reinforcement Learning examples
PPO IMPLEMENTATION ON TENSORFLOW
Reinforcement Learning in Super Mario using Pytorch and PPO
PyTorch application of reinforcement learning Advanced Policy Gradient algorithms in OpenAI BipedalWalker- PPO
PyTorch application of reinforcement learning DDPG and PPO algorithms in Unity 3D-Ball
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