A modular high-level library to train embodied AI agents across a variety of tasks and environments.

Scalable Multi-Agent RL Training School for Autonomous Driving

Reinforcement learning environments with musculoskeletal models

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

A hexapod robot simulator built from first principles

High Fidelity Simulator for Reinforcement Learning and Robotics Research.

API to run VirtualHome, a Multi-Agent Household Simulator

A general-purpose, flexible, and easy-to-use simulator alongside an OpenAI Gym trading environment for MetaTrader 5 trading platform (Approved by OpenAI Gym)

ELM327 Emulator for testing software interfacing OBDII via ELM327 adapter supporting multi-ECU simulation

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.

Simulate firmware with one click of firmadyne (使用 firmadyne 一键模拟固件)

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

V2E: From video frames to DVS events

ELFI - Engine for Likelihood-Free Inference

Python API for BeamNG.tech

A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose

Nanopore sequence read simulator

PCSim: LiDAR Point Cloud Simulation and Sensor Placement! Code of [ICRA 2023] "Analyzing Infrastructure LiDAR Placement with Realistic LiDAR Simulation Library" and [ICCV 2023] "Optimizing the Placement of Roadside LiDARs for Autonomous Driving".

VHDL/Verilog/SystemC code generator, simulator API written in python/c++

OPEM (Open Source PEM Fuel Cell Simulation Tool)