multi-agent

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

A Platform for Many-agent Reinforcement Learning

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control

This is the official implementation of Multi-Agent PPO (MAPPO).

Awesome Game AI materials of Multi-Agent Reinforcement Learning

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

A collection of multi agent environments based on OpenAI gym.

Trajectory Planner in Multi-Agent and Dynamic Environments

Come & try Decision-Intelligence version of "Agar"! Gobigger could also help you with multi-agent decision intelligence study.

Open-Source Framework for Development, Simulation and Benchmarking of Behavior Planning Algorithms for Autonomous Driving

API to run VirtualHome, a Multi-Agent Household Simulator

A framework for autonomous economic agent (AEA) development

Multi-Agent Robotics Simulator

The multi-agent version of TORCS for developing control algorithms for fully autonomous driving in the cluttered, multi-agent settings of everyday life.

Lightweight multi-agent gridworld Gym environment

Block-style programming environment for multi agent system, based on MIT Scratch.

[ICCV21] Official implementation of the "Social NCE: Contrastive Learning of Socially-aware Motion Representations" in PyTorch.

PGDrive: an open-ended driving simulator with infinite scenes from procedural generation

TensorSwarm: A framework for reinforcement learning of robot swarms.

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

Still struggling with the high threshold or looking for the appropriate baseline? Come here and new starters can also play with your own multi-agents!

Continuous CBS - a modification of conflict based search algorithm, that allows to perform actions (move, wait) of arbitrary duration. Timeline is not discretized, i.e. is continuous.

Multi & Single Agent Reinforcement Learning for Traffic Signal Control Problem

Algorithm for prioritized multi-agent path finding (MAPF) in grid-worlds. Moves into arbitrary directions are allowed (each agent is allowed to follow any-angle path on the grid). Timeline is continuous, i.e. action durations are not explicitly discretized into timesteps. Different agents' size and moving speed are supported. Planning is carried out in (x, y, \theta) configuration space, i.e. agents' orientation are taken into account.

A Universal Deep Reinforcement Learning Framework

Mobile Agent that moves on a platform distributed on many machines and recover the mac address of each machine during the deplacement

Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.