- OpenAI Baselines updated: deduplicated code and benchmarks! https://github.com/openai/baselines 3 comments reinforcementlearning
Linking pages
- Dear OpenAI: Please Open Source Your Language Model https://thegradient.pub/openai-please-open-source-your-language-model/ 124 comments
- GitHub - wwxFromTju/awesome-reinforcement-learning-lib: GitHub's code repository is all you need https://github.com/wwxFromTju/awesome-reinforcement-learning-lib 19 comments
- GitHub - Officium/RL-Experiments: High-quality implementations of deep reinforcement learning algorithms for experiments https://github.com/Officium/RL-Experiments 14 comments
- GitHub - zziz/pwc: This repository is no longer maintained. https://github.com/zziz/pwc 13 comments
- GitHub - marload/DeepRL-TensorFlow2: 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2 https://github.com/marload/deep-rl-tf2 10 comments
- RAdam: A New State-of-the-Art Optimizer for RL? | by Chris Nota | Autonomous Learning Library | Medium https://medium.com/autonomous-learning-library/radam-a-new-state-of-the-art-optimizer-for-rl-442c1e830564 10 comments
- Ingredients for Robotics Research https://openai.com/blog/ingredients-for-robotics-research/ 8 comments
- GitHub - qqadssp/PPO-Pytorch: Minimal implementation of PPO, running in Mujoco env, using Gym-mujoco https://github.com/qqadssp/PPO-Pytorch 8 comments
- OpenAI Baselines: ACKTR & A2C https://blog.openai.com/baselines-acktr-a2c/ 6 comments
- GitHub - hill-a/stable-baselines: A fork of OpenAI Baselines, implementations of reinforcement learning algorithms https://github.com/hill-a/stable-baselines 6 comments
- Proximal Policy Optimization https://blog.openai.com/openai-baselines-ppo/ 5 comments
- GitHub - qfettes/DeepRL-Tutorials: Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch https://github.com/qfettes/DeepRL-Tutorials 4 comments
- Playing Atari with deep reinforcement learning - deepsense.ai’s approach - deepsense.ai https://deepsense.ai/playing-atari-with-deep-reinforcement-learning-deepsense-ais-approach/ 3 comments
- GitHub - IBM/rl-testbed-for-energyplus: Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus https://github.com/IBM/rl-testbed-for-energyplus 2 comments
- Teaching a Neural Network to play the Breakout game | by Dmitrii Eliuseev | Dev Genius https://dmitryelj.medium.com/teaching-a-neural-network-to-play-the-breakout-game-793ad7d1b20e 2 comments
- GitHub - vwxyzjn/cleanrl: High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG) https://github.com/vwxyzjn/cleanrl 1 comment
- Using the latest advancements in deep learning to predict stock price movements | by Boris B | Towards Data Science https://towardsdatascience.com/aifortrading-2edd6fac689d#c39d 1 comment
- Trade and Invest Smarter — The Reinforcement Learning Way | by Adam King | Towards Data Science https://towardsdatascience.com/trade-smarter-w-reinforcement-learning-a5e91163f315 1 comment
- GitHub - SforAiDl/genrl: A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL https://github.com/SforAiDl/genrl 1 comment
- The Best Tools for Reinforcement Learning in Python You Actually Want to Try - neptune.ai https://neptune.ai/blog/the-best-tools-for-reinforcement-learning-in-python 0 comments
Linked pages
- Homebrew — The Missing Package Manager for macOS (or Linux) https://brew.sh 184 comments
- GitHub - openai/mujoco-py: MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3. https://github.com/openai/mujoco-py 15 comments
- Install TensorFlow 2 https://www.tensorflow.org/install 7 comments
- MuJoCo — Advanced Physics Simulation http://www.mujoco.org/ 4 comments
- tempfile â Generate temporary files and directories — Python 3.11.1 documentation https://docs.python.org/3/library/tempfile.html 0 comments
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