Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
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.
Deep RL Algotrading with Ray API
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.
An open, minimalist Gymnasium environment for autonomous coordination in wireless mobile networks.
Deep Reinforcement Learning For Trading
An introductory tutorial about leveraging Ray core features for distributed patterns.
Walkthroughs for DSL, AirSim, the Vector Institute, and more
Adaptive real-time traffic light signal control system using Deep Multi-Agent Reinforcement Learning
RLlib tutorials
Dynamic multi-cell selection for cooperative multipoint (CoMP) using (multi-agent) deep reinforcement learning
Reinforcement learning algorithms in RLlib
An open source library for connecting AnyLogic models with Reinforcement Learning frameworks through OpenAI Gymnasium
Tutorial for Ray
An example implementation of an OpenAI Gym environment used for a Ray RLlib tutorial
Exploring learned cooperation, coevolution and free-riding. Learning is achieved through Multi-Agent Deep Reinforcement Learning (MADRL) in an ecological environment. The environment emits no other than sparse reproduction rewards. No reward shaping, no explicit cooperation signal.
Super Mario Bros training with Ray RLlib DQN algorithm
Autonomous driving agent in Carla simulator leveraging IL and RL techniques.
Used Flow, Ray/RLlib and OpenAI Gym to simulate and train autonomous vehicles/human drivers in SUMO (Simulation of Urban Mobility)
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