Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.
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Updated
Sep 18, 2024 - Python
Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.
Incremental Learning with Policy Gradient Methods and Eligibility Traces
Yet another 2048 in reinforcement learning
Car racing RL agents in actual F1 tracks
Reinforcement Learning for the inverted pendulum problem using a custom simulation. Implements and evaluates DQN, REINFORCE, and DDPG algorithms to learn control strategies for balancing a pendulum on a moving cart.
testing MLP, DQN, PPO, SAC, policy-gradient by snakeAI
Advantage Leftover Lunch Reinforcement Learning (A-LoL RL): Improving Language Models with Advantage-based Offline Policy Gradients
An elegant PyTorch deep reinforcement learning library.
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Some algorithms of Reinforcement Learning implemented by me, in accordance to "Introduction to Reinforcement Learning" by Richard Sutton and Andrew Barto.
Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
Explorer is a PyTorch reinforcement learning framework for exploring new ideas.
A collection of my implemented RL agents for games like Pacman, Pong, SpaceInvaders, Frozenlake, Taxi, Pixelcopter, Pyramids and a lot more by implementing various DRL algorithms using gym, unity-ml, pygame, sb3, rl-zoo and pandagym libraries. To see more advanced & interesting agents, please visit below link:
PyTorch implementations for deep and classical rl algorithms
Jaxplorer is a Jax reinforcement learning (RL) framework for exploring new ideas.
Pytorch implementation of twin delayed deep deterministic policy gradients (TD3)
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
[WIP] RL agent for the SuperTuxKart game.
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