Minari
gymprecice
Minari | gymprecice | |
---|---|---|
1 | 1 | |
219 | 20 | |
5.9% | - | |
8.2 | 7.4 | |
2 days ago | 3 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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Minari
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Announcing Minari (Gym for offline RL, by the Farama Foundation) is going into public beta
You can also read the full release notes here: https://github.com/Farama-Foundation/Minari/releases/tag/v0.3.0
gymprecice
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Interesting Physics related RL gym?
Please check our recently released package https://github.com/gymprecice/gymprecice. There are couple of example there for active flow control and FSI. Gym-preCICE is a Python preCICE adapter fully compliant with Gymnasium (also known as OpenAI Gym) API to facilitate designing and developing Reinforcement Learning (RL) environments for single- and multi-physics active flow control (AFC) applications. In an actor-environment setting, Gym-preCICE takes advantage of preCICE, an open-source coupling library for partitioned multi-physics simulations, to handle information exchange between a controller (actor) and an AFC simulation environment. The developed framework results in a seamless non-invasive integration of realistic physics-based simulation toolboxes with RL algorithms.
What are some alternatives?
d3rlpy - An offline deep reinforcement learning library
MO-Gymnasium - Multi-objective Gymnasium environments for reinforcement learning
exorl - ExORL: Exploratory Data for Offline Reinforcement Learning
gym-simplegrid - Simple Gridworld Gymnasium Environment
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
gym-hybrid - Collection of OpenAI parametrized action-space environments.
gym-cartpole-swingup - A simple, continuous-control environment for OpenAI Gym
Gym-Stag-Hunt - A custom reinfrocement learning environment for OpenAI Gym & PettingZoo that implements various Stag Hunt-like social dilemma games.
modelicagym - Modelica models integration with Open AI Gym