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udacity / deep-reinforcement-learning

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README doesn't reference required Visual Studio Build Tools for Windows

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daniel-fudge
daniel-fudge commented Sep 2, 2019

The OpenAI Gym installation instructions are missing reference to the "Build Tools for Visual Studio 2019" from the following site.

https://visualstudio.microsoft.com/downloads/

I also found this by reading the following article.
https://towardsdatascience.com/how-to-install-openai-gym-in-a-windows-environment-338969e24d30

Even though this is an issue in the OpenAI gym, a note in this RE

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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

sudharsan13296 / Hands-On-Reinforcement-Learning-With-Python

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Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
reinforcement-learning monte-carlo deep-reinforcement-learning openai-gym q-learning deep-learning-algorithms policy-gradient sarsa deep-q-network markov-decision-processes asynchronous-advantage-actor-critic double-dqn trpo dueling-dqn deep-deterministic-policy-gradient ppo deep-recurrent-q-network drqn hindsight-experience-replay policy-gradients
  • Updated Apr 17, 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

rlgraph / rlgraph

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[Core] Improve naming/documentation of IR

michaelschaarschmidt
michaelschaarschmidt commented Dec 28, 2018

Understanding the build process is currently quite difficult because it happens partly in the graph builder, in static and non-static parts of Component, and in various utils.

We should:

  • Make fully clear the purpose of each build Op
  • Fully document the Structure of the IR generated by the two builds (potentially revive visualisation project for this)
  • Clarify the use of Build ops in gra
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