AgentIndex icon
AgentIndex
skrl logo
skrl
★ 1.1k
vs
virtualhome logo
virtualhome
★ 644

skrl vs virtualhome

skrl: skrl is an open-source, modular Reinforcement Learning library implemented in Python, supporting PyTorch, JAX, and NVIDIA Warp. It focuses on modularity, readability, simplicity, and transparent algorithm implementation, also supporting various environment interfaces like Gym, Gymnasium, and Isaac Lab.; virtualhome: VirtualHome is an interactive platform designed to simulate complex household activities using programs and a Python API. It supports rich environmental interactions, multi-agent activities, and serves as an environment for embodied AI and reinforcement learning agent training.

01

TL;DR

skrl logo
skrlLLM Infra · ★ 1.1k

Developing and testing new Reinforcement Learning algorithms

Read skrl full review →
virtualhome logo
virtualhomeVision / Multimodal · ★ 644

Training agents for embodied AI and Reinforcement Learning tasks.

Read virtualhome full review →
02

Side-by-Side Comparison

Field
skrl logoskrl
virtualhome logovirtualhome
Category
LLM Infra
Vision / Multimodal
Stars
★ 1.1k
★ 644
License
MIT
MIT
Install Command
pip install skrl
pip install virtualhome
Updated
1d ago
5mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Reinforcement Learning, Python, PyTorch
Simulation, Embodied AI, Reinforcement Learning
03

Features

skrl logoskrl
01Modular and extensible design
02Transparent algorithm implementation
03Multi-framework support (PyTorch, JAX, NVIDIA Warp)
04Compatibility with various environment interfaces (Gym, Gymnasium, PettingZoo, ManiSkill)
05Simultaneous training in NVIDIA Isaac Lab and MuJoCo Playground with scope-based resource sharing
virtualhome logovirtualhome
01Simulates complex household activities through programs via a Python API.
02Enables rich interactions with the environment, including picking up objects and operating appliances.
03Features procedural generation to create an infinite variety of unique environments.
04Supports multi-agent activities and allows dynamic modification of environments.
05Provides streaming of ground-truth data (segmentation, optical flow, depth) and OpenAI Gym-like RL environments.
04

Use Cases

skrl logoskrl
↳Developing and testing new Reinforcement Learning algorithms
↳Training AI agents in various simulated environments (e.g., robotic control, game AI)
↳Research in Reinforcement Learning leveraging multiple backend frameworks
virtualhome logovirtualhome
↳Training agents for embodied AI and Reinforcement Learning tasks.
↳Simulating and visualizing complex household activities through programs.
↳Generating large-scale datasets of programs and environment states for research.
05

Best For

skrl logoskrl
EssentialTrending
virtualhome logovirtualhome
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FAQ

FAQ

What is the difference between skrl and virtualhome?
Both skrl and virtualhome are in the LLM Infra category. skrl has 1.1k stars, while virtualhome has 644 stars.
Which is better, skrl or virtualhome?
The best choice depends on your use case. Choose skrl if Developing and testing new Reinforcement Learning algorithms, and virtualhome if Training agents for embodied AI and Reinforcement Learning tasks..
Is skrl free or open source?
Yes, skrl is open source on GitHub (MIT).
Is virtualhome free or open source?
Yes, virtualhome is open source on GitHub (MIT).
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Related

Alternatives to skrl →Alternatives to virtualhome →skrl details →virtualhome details →