Popular GitHub Repositories for Cartpole

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

Solving OpenAI Gym problems.

Simple Cartpole example writed with pytorch.

A collection of Deep Reinforcement Learning algorithms implemented with PyTorch to solve Atari games and classic control tasks like CartPole, LunarLander, and MountainCar.

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

Upside-Down Reinforcement Learning (⅂ꓤ) implementation in PyTorch. Based on the paper published by Jürgen Schmidhuber.

Deep Reinforcement Learning by using Proximal Policy Optimization and Random Network Distillation in Tensorflow 2 and Pytorch with some explanation

This Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.

Usage of genetic algorithms to train a neural network in multiple OpenAI gym environments.

CartPole game by Reinforcement Learning, a journey from training to inference

NeurIPS 2019: DQN(λ) = Deep Q-Network + λ-returns.

WIP implementation of Probabilistic Differential Dynamic Programming in PyTorch

Collection of my Reinforcement Learning (RL) practices including DQN, D3QN, and Adaptive Gamma, applied to the Lunar Lander and CartPole environments. ??️

Deep Reinforcement Learning with CartPole in Pytorch

A concise PyTorch implementation of Proximal Policy Optimization(PPO) solving CartPole-v0

Experiments of the three PPO-Algorithms (PPO, clipped PPO, PPO with KL-penalty) proposed by John Schulman et al. on the 'Cartpole-v1' environment.

PyTorch implementation of DQN

GAIL learning to imitate PPO playing CartPole.