football
dmc2gymnasium
football | dmc2gymnasium | |
---|---|---|
2 | 1 | |
3,253 | 4 | |
0.6% | - | |
0.0 | 3.4 | |
6 months ago | 19 days ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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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 :-
dmc2gymnasium
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DM Control Suite vs. Original Environments
I'm actually working on a DMC to gymnasium wrapper right now that you might find useful https://github.com/imgeorgiev/dmc2gymnasium
What are some alternatives?
robo-gym - An open source toolkit for Distributed Deep Reinforcement Learning on real and simulated robots.
gym-simplegrid - Simple Gridworld Gymnasium Environment
space-gym - Challenging reinforcement learning environments with locomotion tasks in space
Gym-Trading-Env - A simple, easy, customizable Gymnasium environment for trading.
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.
pysc2 - StarCraft II Learning Environment
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).
policy-adaptation-during-deployment - Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
envpool - C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
holodeck - High Fidelity Simulator for Reinforcement Learning and Robotics Research.
skrl - Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Isaac Orbit and Omniverse Isaac Gym