AgentIndex icon
AgentIndex
rlcard logo
rlcard
★ 3.6k
vs
skrl logo
skrl
★ 1.1k

rlcard vs skrl

rlcard: RLCard is a toolkit designed for Reinforcement Learning in card games, providing multiple card environments with easy-to-use interfaces. Its goal is to bridge reinforcement learning and imperfect information games, supporting various RL and searching algorithms.; 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.

01

TL;DR

rlcard logo
rlcardLLM Infra · ★ 3.6k

Developing and testing reinforcement learning agents for various card games.

Read rlcard full review →
skrl logo
skrlLLM Infra · ★ 1.1k

Developing and testing new Reinforcement Learning algorithms

Read skrl full review →
02

Side-by-Side Comparison

Field
rlcard logorlcard
skrl logoskrl
Category
LLM Infra
LLM Infra
Stars
★ 3.6k
★ 1.1k
License
MIT
MIT
Install Command
pip3 install rlcard
pip install skrl
Updated
2y ago
2d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Reinforcement Learning, Card Games, Imperfect Information Games
Reinforcement Learning, Python, PyTorch
03

Features

rlcard logorlcard
01Provides multiple card game environments for research and development.
02Offers easy-to-use interfaces for implementing various reinforcement learning and search algorithms.
03Supports popular algorithms such as Deep Q-Learning (DQN), NFSP, CFR, and Deep Monte-Carlo (DMC).
04Integrates with PettingZoo and provides PyTorch implementations for training algorithms.
05Includes human interfaces for interactive play and a GUI demo (RLCard-Showdown) for visualization.
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
04

Use Cases

rlcard logorlcard
↳Developing and testing reinforcement learning agents for various card games.
↳Conducting research into strategies and algorithms within imperfect information game environments.
↳Comparing the performance and effectiveness of different RL and search algorithms.
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
05

Best For

rlcard logorlcard
—
skrl logoskrl
EssentialTrending
FAQ

FAQ

What is the difference between rlcard and skrl?
Both rlcard and skrl are in the LLM Infra category. rlcard has 3.6k stars, while skrl has 1.1k stars.
Which is better, rlcard or skrl?
The best choice depends on your use case. Choose rlcard if Developing and testing reinforcement learning agents for various card games., and skrl if Developing and testing new Reinforcement Learning algorithms.
Is rlcard free or open source?
Yes, rlcard is open source on GitHub (MIT).
Is skrl free or open source?
Yes, skrl is open source on GitHub (MIT).
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Related

Alternatives to rlcard →Alternatives to skrl →rlcard details →skrl details →