gym VS baselines

Compare gym vs baselines and see what are their differences.

gym

A toolkit for developing and comparing reinforcement learning algorithms. (by openai)

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms (by openai)
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gym baselines
96 14
33,750 15,255
0.8% 0.8%
0.0 0.0
about 1 month ago 4 months ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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gym

Posts with mentions or reviews of gym. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-25.

baselines

Posts with mentions or reviews of baselines. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-03.
  • How to proceed further? (Learning RL)
    3 projects | /r/reinforcementlearning | 3 Oct 2022
    Ah sorry I understood your post. It has helped me to code quite a few of them from scratch but you can also check out https://github.com/openai/baselines or similar
  • How to tune hypeparametes in A2C-ppo?
    2 projects | /r/reinforcementlearning | 15 Jun 2022
    Im currently working with A2C. The model was able to learn open ai pong, i ran this as a sanity check that i havent made any bugs. Now im trying to make the model play breakout, but still after 10m steps the model has not made any significant progress. Im using baseline hyperparameters which can be found here https://github.com/openai/baselines/blob/master/baselines/a2c/a2c.py, except my buffersize have been from 512 to 4096. Ive noticed that entropy decreases extremely slowly given the buffersize from the interval which i just gave. So my questions are how to make entropy decrease and how to increase rewards per buffer? Ive tried to decrease the entropy coefficient to almost zero, but still it acts very weirdly.
  • Boycotting 2.0 or rather PoS
    2 projects | /r/EtherMining | 15 May 2021
    I used a multitude of agents to train it but the best I found was A3C, there are a bunch of examples here you can use to test their performance (although they may require some tweaking).
  • How to speed up off-policy algorithms?
    2 projects | /r/reinforcementlearning | 21 Apr 2021
    I noticed that off-policy algorithms including DQN, DDPG and TD3 in different baselines and stable-baselines are implemented with a single environment. And even if more environments were added, this won't affect performance because this will only be adding more fresh samples to replay buffer(s). What are some ways to improve speed without major changes to the algorithms? The only thing that I could think of is adding an on-policy update like in ACER but this is going to change the algorithms and I don't know whether it will improve/worsen model convergence.
  • Any beginner resources for RL in Robotics?
    3 projects | /r/robotics | 19 Apr 2021
    OpenAI baselines https://github.com/openai/baselines
  • Convergence of the PPO
    2 projects | /r/reinforcementlearning | 27 Mar 2021
    It might be worth comparing your implementation to the DeepMind PPO1 & 2 ones to see if they have the same side effect: https://github.com/openai/baselines

What are some alternatives?

When comparing gym and baselines you can also consider the following projects:

ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

carla - Open-source simulator for autonomous driving research.

tensorflow - An Open Source Machine Learning Framework for Everyone

dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.

gensim - Topic Modelling for Humans