rllib

There are 86 repositories under rllib topic.

  • ray-project/ray

    Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

    Language:Python39k49121.1k6.8k

  • Replicable-MARL/MARLlib

    One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

    Language:Python1.2k10158179
  • VectorizedMultiAgentSimulator

    proroklab/VectorizedMultiAgentSimulator

    VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

    Language:Python46076390
  • T-1000

    Draichi/T-1000

    :zap: :zap: π˜‹π˜¦π˜¦π˜± π˜™π˜“ 𝘈𝘭𝘨𝘰𝘡𝘳𝘒π˜₯π˜ͺ𝘯𝘨 𝘸π˜ͺ𝘡𝘩 π˜™π˜’π˜Ί π˜ˆπ˜—π˜

    Language:Python176202142

  • ChuaCheowHuan/gym-continuousDoubleAuction

    A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

    Language:Jupyter Notebook1507131

  • stefanbschneider/mobile-env

    An open, minimalist Gymnasium environment for autonomous coordination in wireless mobile networks.

    Language:Python13222231

  • druce/rl

    Deep Reinforcement Learning For Trading

    Language:Jupyter Notebook1064327

  • DerwenAI/ray_tutorial

    An introductory tutorial about leveraging Ray core features for distributed patterns.

    Language:Jupyter Notebook787426

  • JacopoPan/a-minimalist-guide

    Walkthroughs for DSL, AirSim, the Vector Institute, and more

    Language:C++721113

  • DerwenAI/rllib_tutorials

    RLlib tutorials

    Language:Jupyter Notebook66318

  • goshaQ/adaptive-tls

    Adaptive real-time traffic light signal control system using Deep Multi-Agent Reinforcement Learning

    Language:Python661215

  • CN-UPB/DeepCoMP

    Dynamic multi-cell selection for cooperative multipoint (CoMP) using (multi-agent) deep reinforcement learning

    Language:Python646315

  • 0xangelo/raylab

    Reinforcement learning algorithms in RLlib

    Language:Python594510

  • MarcEscandell/ALPypeRL

    An open source library for connecting AnyLogic models with Reinforcement Learning frameworks through OpenAI Gymnasium

    Language:Python36134

  • DerwenAI/gym_example

    An example implementation of an OpenAI Gym environment used for a Ray RLlib tutorial

    Language:Python352220

  • OpenRL-Lab/Ray_Tutorial

    Tutorial for Ray

    Language:Python29104

  • AhmetFurkanDEMIR/SuperMarioBrosRL

    Super Mario Bros training with Ray RLlib DQN algorithm

    Language:Python26203

  • doesburg11/PredPreyGrass

    Intelligent Artificial Life. Researching behavior by nature and nurture simulation, deploying multi-agent reinforcement learning and evolving generational inheritance.

    Language:Python24644
  • AutonomousVehicleSimulation

    rlew631/AutonomousVehicleSimulation

    Used Flow, Ray/RLlib and OpenAI Gym to simulate and train autonomous vehicles/human drivers in SUMO (Simulation of Urban Mobility)

    Language:Jupyter Notebook24104

  • nicofirst1/rl_werewolf

    RL environment replicating the werewolf game to study emergent communication

    Language:Python20102

  • EKostinoudis/Carla_Autonomous_Driving

    Autonomous driving agent in Carla simulator leveraging IL and RL techniques.

    Language:Python19115

  • kochlisGit/Shadow-Hand-Controller

    Construction of controllers for Shadow-Hand in Mujoco environment, using Deep Learning. 2 Different methods were used to create the controllers: a) Behavioral Cloning b) Deep Reinforcement Learning

    Language:Python16213

  • openpsi-projects/srl

    SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores

    Language:Python15301

  • michaelfeil/skyjo_rl

    Multi-Agent Reinforcement Learning Environment for the card game SkyJo, compatible with PettingZoo and RLLIB

    Language:Jupyter Notebook14110

  • akirasosa/aie-train

    AI Economist Training Examples

    Language:Python12134

  • elliottower/gobblet-rl

    Interactive Multi-Agent Reinforcement Learning Environment for the board game Gobblet using PettingZoo.

    Language:Python12100

  • isk03276/LearnToMoveUR3

    Learning various robotic manipulations tasks of the UR3

    Language:Python12142

  • dcos-labs/dcos-jupyterlab-service

    JupyterLab Notebook for Mesosphere DC/OS

    Language:Shell117911

  • HumanCompatibleAI/better-adversarial-defenses

    Training in bursts for defending against adversarial policies

    Language:Python11413

  • Nullspace-Colombia/unray-rllib

    Rllib framework for using Unreal Engine 5 (UE5) as external environment for Reinforced Learning training process

    Language:Python11331

  • eescriba/smart-cities-drl

    Urban mobility simulations with Python3, RLlib (Deep Reinforcement Learning), Mesa (Agent-based modeling) and OpenAI Gym.

    Language:Jupyter Notebook10113

  • kochlisGit/Deep-RL-Frameworks

    Comparison of different Deep Reinforcement Learning (DRL) Frameworks. This repository includes "tf-agents", "RLlib" and will soon support "acme" as well.

    Language:Jupyter Notebook9100

  • Wadaboa/cpr-appropriation

    Solutions to the Harvest CPR appropriation problem with policy gradient methods and social learning, for Autonomous and Adaptive Systems class at UNIBO

    Language:Python9104

  • elliottower/cathedral-rl

    Interactive Multi-Agent Reinforcement Learning Environment for the board game Cathedral using PettingZoo

    Language:Python8100

  • Engineering-Geek/RL-UAV

    Reinforcement Learning for Unmanned Airial Vehicles

    Language:Python8100

  • marketsAI/marketsAI

    A modular framework designed to simulate economies and markets using Reinforcement Learning.

    Language:Jupyter Notebook8211