Gym-Trading-Env VS gym-simplegrid

Compare Gym-Trading-Env vs gym-simplegrid and see what are their differences.

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Gym-Trading-Env gym-simplegrid
2 2
237 33
- -
4.4 5.4
21 days ago 19 days ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Gym-Trading-Env

Posts with mentions or reviews of Gym-Trading-Env. We have used some of these posts to build our list of alternatives and similar projects.

gym-simplegrid

Posts with mentions or reviews of gym-simplegrid. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-12.

What are some alternatives?

When comparing Gym-Trading-Env and gym-simplegrid you can also consider the following projects:

freqtrade-gym - A customized gym environment for developing and comparing reinforcement learning algorithms in crypto trading.

minihack - MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research

gym-mtsim - A general-purpose, flexible, and easy-to-use simulator alongside an OpenAI Gym trading environment for MetaTrader 5 trading platform (Approved by OpenAI Gym)

dmc2gymnasium - Gymnasium integration for the DeepMind Control (DMC) suite

Minigrid - Simple and easily configurable grid world environments for reinforcement learning

loopquest - A Production Tool for Embodied AI

santorini-RL - Play the board game Santorini with this Reinforcement Learning agent and custom Gym environment

pyreason-gym - An OpenAI wrapper for PyReason to use in a Grid World reinforcement learning setting

gymprecice - A framework to design and develop reinforcement learning environments for single- and multi-physics active flow control.

space-gym - Challenging reinforcement learning environments with locomotion tasks in space

pyTORCS-docker - Docker-based, gym-like torcs environment with vision.