Public release of Track-to-Learn: A general framework for tractography with deep reinforcement learning
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Updated
Jun 5, 2024 - Python
Public release of Track-to-Learn: A general framework for tractography with deep reinforcement learning
Base of CraftGround, ⚡⚡ Lightning-Fast Minecraft Reinforcement Learning environment based on fabric
A ScalaPy Facade for OpenAI Gym!
Sotopia: an Open-ended Social Learning Environment (ICLR 2024 spotlight)
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.
Reinforcement Learning through Tree-of-Thought (ToT) with pure math
FurnitureBench: Real-World Furniture Assembly Benchmark (RSS 2023)
Procedural Environment Generation for Accelerated Multi-Agent Reinforcement Learning
The Core Reinforcement Learning library is intended to enable scalable deep reinforcement learning experimentation in a manner extensible to new simulations and new ways for the learning agents to interact with them. The hope is that this makes RL research easier by removing lock-in to particular simulations.The work is released under the follow…
Gym environment for building simulation and control using reinforcement learning
This repo contains a curative list of robot learning (mainly for manipulation) resources.
Reinforcement learning environments for planar robotics based on MuJoCo
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Simple Gridworld Gymnasium Environment
Realistic RL environments for vehicle fleets
Connect 4 (X) Environment + GYM + PyGame GUI
An easy-to-use and modular Python library for the Job Shop Scheduling Problem (JSSP)
Grid2Op a testbed platform to model sequential decision making in power systems.
C++ wrappers of OpenAI-Gym environments
Extended, multi-agent and multi-objective (MaMoRL) environments based on DeepMind's AI Safety Gridworlds. This is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents. It is made compatible with OpenAI's Gym/Gymnasium and Farama Foundation PettingZoo.
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