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22 search results found

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A parallel framework for population-based multi-agent reinforcement learning.

Pokerrl ⭐ 380

Framework for Multi-Agent Deep Reinforcement Learning in Poker

Rlgraph ⭐ 241

RLgraph: Modular computation graphs for deep reinforcement learning

Multi Commander ⭐ 92

Multi & Single Agent Reinforcement Learning for Traffic Signal Control Problem

Distributedrl ⭐ 84

A framework for easy prototyping of distributed reinforcement learning algorithms

Db Football ⭐ 80

A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.

A platform to test reinforcement learning policies in the datacenter setting.

Deepcomp ⭐ 36

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

Godot_gym_api ⭐ 27

Godot Gym API is an Open Source framework for using Godot3 game engine as 3d-environment for training reinforcement learning agents implemented in Python on any data, including images and point clouds.

Rllib Energyplus ⭐ 25

Simple EnergyPlus environments for control optimization using reinforcement learning

Alpyperl ⭐ 20

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

Graph Env ⭐ 20

Reinforcement learning for combinatorial optimization over directed graphs

Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"

Distributed Drl ⭐ 17

Distributed Deep Reinforcement Learning

Gym_example ⭐ 15

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

Rayenvwrapper ⭐ 15

OpenAi's gym environment wrapper to vectorize them with Ray

Marlware ⭐ 11

Repository dedicated to developing a robust and modular framework for Multi-Agent Reinforcement Learning (MARL) algorithms.

Evolution Strategies ⭐ 8

🤖Distributed Natural Evolution Strategies Build with PyTorch and Ray

Comyx is an optimized and modular Python library for simulating wireless communication systems.

Neurips2018 Aiforprosthetics ⭐ 6

Reinforcement learning with musculoskeletal models

Dhc Robust Mapf ⭐ 6

Learnable MAPF. “Distributed Heuristic Multi-Agent Path Finding with Communication” (DHC) algorithm from ICRA 2021 is implemented and benchmarked in out-of-distribution (OOD) scenarios. A new robust training loop to handle communication failures is introduced.

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