Jiminy: a fast and portable Python/C++ simulator of poly-articulated robots with OpenAI Gym interface for reinforcement learning
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Updated
May 14, 2024 - Jupyter Notebook
Jiminy: a fast and portable Python/C++ simulator of poly-articulated robots with OpenAI Gym interface for reinforcement learning
FinRL: Financial Reinforcement Learning. 🔥
Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Isaac Orbit and Omniverse Isaac Gym
C++ wrappers of OpenAI-Gym environments
In questa repository una collezione di tutorial sulle basi del Reinforcement Learning, sviluppati in Python, interamente in italiano.
Gym Electric Motor (GEM): An OpenAI Gym Environment for Electric Motors
Reinforcement Learning Algorithms in a simple Gridworld
Texas holdem OpenAi gym poker environment with reinforcement learning based on keras-rl. Includes virtual rendering and montecarlo for equity calculation.
A collection of multi agent environments based on OpenAI gym.
For trading. Please star.
Train quadruped locomotion using reinforcement learning in Mujoco
Global Markets Options Pricing
Deep reinforcement learning for smart calibration of radio telescopes. Automatic hyper-parameter tuning.
Self-driving car simulator for the Duckietown universe
A Catkin workspace designed to simplify the setup and use of the ROS Gazebo Gym framework.
The project focuses on motion planning for a wide range of robotic structures using deep reinforcement learning (DRL) algorithms to solve the problem of reaching a static or random target within a pre-defined configuration space.
Framework for integrating ROS and Gazebo with gymnasium, streamlining the development and training of RL algorithms in realistic robot simulations.
Wesendrup, Kevin; Hellingrath, Bernd (2023): ML2-enabled Condition-based Demand, Production, Inventory, and Maintenance Planning. In : IFAC World Congress 2023. IFAC World Congress 2023, pp. 7182–7187.
A bare-bones Python library for quality diversity optimization.
Theories and code related to Deep learning topics involved in Reinforcement learning
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