🔋 Datasets with baselines for offline multi-agent reinforcement learning.
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Updated
May 14, 2024 - Python
🔋 Datasets with baselines for offline multi-agent reinforcement learning.
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
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.
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
The Drone Swarm Search project provides an environment for SAR missions built on PettingZoo, where agents, represented by drones, are tasked with locating targets identified as shipwrecked individuals.
A collection of MARL benchmarks based on TorchRL
A multi-agent deep reinforcement learning model to de-traffic our lives
Official codebase for Generating Diverse Cooperative Agents by Learning Incompatible Policies (notable-top-25% @ ICLR 2023)
DI-engine docs (Chinese and English)
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Safe Multi-Agent Reinforcement Learning to Make decisions in Autonomous Driving
Boid flock multi-agent RL training environment implemented in JAX
Intelligent Social Systems and Swarm Robotics Lab (IS3R)
Algorithms to solve the DSSE environment, focusing on optimizing drone swarm search and navigation for critical applications.
This project simulates a virtual war between n RL-reasoning (Q-learning) agents.
Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat
A tool for aggregating and plotting MARL experiment data.
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