Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
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Updated
Mar 31, 2024 - Python
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
An elegant PyTorch deep reinforcement learning library.
Modularized Implementation of Deep RL Algorithms in PyTorch
Clean, Robust, and Unified PyTorch implementation of popular DRL Algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map
Repository for codes of 'Deep Reinforcement Learning'
Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.
An RL model that uses double deep Q learning to generate an optimal policy of stock market trades
Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
Pytorch implementation of distributed deep reinforcement learning
Solving board games like Connect4 using Deep Reinforcement Learning
This is an implementation of Deep Q Learning (DQN) playing Breakout from OpenAI's gym with Keras.
A Reinforcement Learning agent to perform overtaking action using Double DQN based CNNs which takes images as input built using TensorFlow.
PyTorch implementation of various reinforcement learning algorithms
A clean framework and implementations for reinforcement learning algorithms.
An AI agent that use Double Deep Q-learning to teach itself to land a Lunar Lander on OpenAI universe
Recommendation System using Deep Q-Networks and Double Deep Q-Networks
Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym
Applying the DQN-Agent from keras-rl to Starcraft 2 Learning Environment and modding it to to use the Rainbow-DQN algorithms.
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