#Reinforcement-learning-environments
Showing 15 of 15 repositories tagged #reinforcement-learning-environments, ranked by stars
Evaluate and improve models and agents using environments
High Fidelity Simulator for Reinforcement Learning and Robotics Research.
A simple, easy, customizable Gymnasium environment for trading.
Turn any song into playable piano sheet music. Paste a YouTube link or upload audio — get a PDF score. Open-source pipeline: Basic Pitch transcription, two-hand arrangement, RL-trained engraving.
OSS RL environment + evals toolkit
This repo contains a curative list of robot learning (mainly for manipulation) resources.
TensorTrade-NG is an open source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning.
A modular Python library for creating, solving, and visualizing job shop scheduling problems.
An OpenAI Gym environment for multi-agent car racing based on Gym's original car racing environment.
AI4U is a plugin that allows you use the Godot Game Engine to specify agents with reinforcement learning. Non-Player Characters (NPCs) of games can be designed using ready-made components.
sharpe is a unified, interactive, general-purpose environment for backtesting or applying machine learning(supervised learning and reinforcement learning) in the context of quantitative trading
Implementation of algorithmic trading using reinforcement learning.
[ICLR 25 Spotlight] A testbed for agents and environments that can automatically improve models through data generation.
Rust and Python Ethereum Agent Based Modelling Library
Rust Market Simulation Library with a Python API