Software Alternatives & Reviews

OpenAI Gym VS Sabaki

Compare OpenAI Gym VS Sabaki and see what are their differences

OpenAI Gym logo OpenAI Gym

OpenAI GYM is a toolkit developers use to both develop and compare reinforcement learning algorithms. Their GitHub repository includes dozens of contributors... read more.

Sabaki logo Sabaki

Sabaki is cross-platform graphical UI for Go/Baduk/Weiqi game board and SGF (Smart Go Format) editor. Free, open source, based on Electron.
  • OpenAI Gym Landing page
    Landing page //
    2023-03-15
  • Sabaki Landing page
    Landing page //
    2020-09-20

OpenAI Gym videos

Keras Q-Learning in the OpenAI Gym (12.3)

More videos:

  • Tutorial - [ROS tutorial] OpenAI Gym For ROS based Robots 101. Gazebo Simulator

Sabaki videos

AikidoTai Sabaki review

More videos:

  • Tutorial - Go Software: How to use KataGo with Sabaki
  • Review - Nick Sibicky Go Lecture #239 - Sabaki

Category Popularity

0-100% (relative to OpenAI Gym and Sabaki)
Data Science And Machine Learning
Online Games
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Games
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, OpenAI Gym should be more popular than Sabaki. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OpenAI Gym mentions (12)

  • 5 Best Places to Use and Try AI Online
    OpenAI Gym: If you're interested in using AI for machine learning, OpenAI Gym (https://gym.openai.com/) is a great resource. It's a platform that provides a wide range of environments and tools for developing and testing machine learning algorithms. You can use it to experiment with different techniques and see how well they perform. Source: over 1 year ago
  • Why GPUs are great for Reinforcement Learning?
    Open source toolkits such as Open AI Gym can be used for developing and comparing reinforcement learning algorithms. - Source: dev.to / about 2 years ago
  • [D] Have there been successful applications of Deep RL to real problems other than board games/Atari?
    There is a lot of work in games, particularly board games, but these do not really solve something "useful" for society. I have seen also lots of toy examples with libraries like gym and some robotics but in general these are rather proof-of-concept models or just models that do not work at all. One that actually does work is Solving Rubik’s Cube with a Robot Hand. This is pretty cool, but again, the domain... Source: about 2 years ago
  • Environments to Test Algorithms (Specifically Genetic Algorithms)
    I haven't used it, but assume https://gym.openai.com/ is exactly for this. Source: about 2 years ago
  • [N] Gym now has a documentation website
    I know it's not a good website but I thought https://gym.openai.com/ was the documentation, is it not? Source: about 2 years ago
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Sabaki mentions (8)

  • I wonder if these ChatGPT answers will every get nuked
    I've been using ChatGPT since launch and constantly seeking out examples of how others have been using it. A few years ago I started using KataGo with Sabaki to improve my go-playing abilities. I've known about token embeddings in neural networks before ChatGPT was a twinkle in OpenAI's eye. I was there, but I haven't seen everything you've seen, so please show me. If the truth is that ChatGPT has canned responses... Source: about 1 year ago
  • Tough semeai during one of my recent tournament games. Black to play and kill the triangled group.
    It's a feature with sabaki, to make it look resemble a real board more. Source: about 1 year ago
  • Learning to score a game.
    That said, if you can download some sgfs and view them in a tool like [sabaki]((https://sabaki.yichuanshen.de/), you can try and match the score that the computer reports. You can get SGFs from here - other sources are available. Be sure to find games which were won on points. You can't count a game won by resignation. Source: over 1 year ago
  • Contributing to open-source go projects?
    It's a shame because KGS would benefit greatly from a modern client. I think at this point writing a new client from scratch would be preferable, or maybe taking something like [Sabaki](https://sabaki.yichuanshen.de/) and turning it into a KGS client might be viable. Speaking of which, Sabaki is a good option for those looking to contribute to an open source project. Source: over 1 year ago
  • DeepMind's Player of Games, a general-purpose game algorithm
    You can also just download pre-trained models. Get those set up and then install Sabaki (https://sabaki.yichuanshen.de/) and connect it to your KataGo... Instant (ok, a few hours probably if it's your first time setting it up) superhuman Go AI. There's even an npm package you can use to process SGF files and automatically score moves as good/questionable/bad + generate variations that were better choices:... - Source: Hacker News / over 2 years ago
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What are some alternatives?

When comparing OpenAI Gym and Sabaki, you can also consider the following products

OpenCV - OpenCV is the world's biggest computer vision library

KaTrain - Improve your go by training with KataGo.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

OGS - Play go/weiqi/baduk online

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

SmartGo - Software for the game of Go, with apps for iPhone, iPad, Mac, and Windows.