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ikostrikov / pytorch-a2c-ppo-acktr-gail

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PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

reinforcement-learning deep-learning deep-reinforcement-learning pytorch atari hessian second-order continuous-control actor-critic ale mujoco proximal-policy-optimization ppo advantage-actor-critic a2c acktr natural-gradients roboschool kfac kronecker-factored-approximation
  • Updated Mar 3, 2020
  • Python

qfettes / DeepRL-Tutorials

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Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

reinforcement-learning gae deep-reinforcement-learning rainbow python3 pytorch deep-q-network actor-critic double-dqn quantile-regression dueling-dqn categorical-dqn ppo advantage-actor-critic a2c deep-recurrent-q-network prioritized-experience-replay multi-step-learning noisy-networks deeprl-tutorials
  • Updated Feb 21, 2020
  • Jupyter Notebook

TianhongDai / reinforcement-learning-algorithms

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This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

algorithm deep-learning atari2600 flappy-bird deep-reinforcement-learning pytorch dqn ddpg sac actor-critic trpo dueling-dqn trust-region-policy-optimization proximal-policy-optimization ppo a2c soft-actor-critic
  • Updated Nov 15, 2019
  • Python

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