football
space-gym
| football | space-gym | |
|---|---|---|
| 2 | 1 | |
| 3,253 | 7 | |
| 0.6% | - | |
| 0.0 | 4.2 | |
| 6 months ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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football
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Creating a new football game
For fun, merging such an idea with Google's open source football research project and its AI could result in a very interesting game!
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How to find which Manjaro package corresponds to which Debian packages?
So I switched to Manjaro from Ubuntu quite some time ago and I am loving the decision whenever I have to build an application there are a bunch of required packages that the application to build is dependent on. But as Debian-based distros are the most popular, the packages are listed as in the Debian Repository. So is there a way I can find which package in Manjaro Repository corresponds to the one in the Debian Repositories as the names of the packages are usually different. Like I was recently trying to install google-research football on my machine and there were the following packages listed as dependencies :-
space-gym
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Simple continuous environment with spaceship but yet challenging for RL algorithms (like SAC, TD3)
In case you want to take a look the envs are published here https://github.com/MIMUW-RL/space-gym
What are some alternatives?
robo-gym - An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots.
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Gym-Trading-Env - A simple, easy, customizable Gymnasium environment for trading.
dmc2gymnasium - Gymnasium integration for the DeepMind Control (DMC) suite
holodeck - High Fidelity Simulator for Reinforcement Learning and Robotics Research.
ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
modelicagym - Modelica models integration with Open AI Gym
alf - Agent Learning Framework https://alf.readthedocs.io
gym-cartpole-swingup - A simple, continuous-control environment for OpenAI Gym