AgentIndex icon
AgentIndex
ir-sim logo
ir-sim
★ 1.2k
vs
on-policy logo
on-policy
★ 2.1k

ir-sim vs on-policy

ir-sim: IR-SIM is an open-source, Python-based robot simulator tailored for navigation, control, and reinforcement learning. It offers a lightweight, user-friendly framework for rapid prototyping with built-in collision detection, ideal for academic and educational purposes.; on-policy: This repository implements MAPPO, a multi-agent variant of PPO, widely used in cooperative multi-agent games and research. It provides robust implementations for various multi-agent environments like StarCraft II, Hanabi, and Google Research Football, along with detailed training scripts and hyperparameter guidance.

01

TL;DR

ir-sim logo
ir-simLLM Infra · ★ 1.2k

Simulating multi-robot collision avoidance strategies and group behaviors.

Read ir-sim full review →
on-policy logo
on-policyLLM Infra · ★ 2.1k

Research and experimentation in cooperative multi-agent reinforcement learning

Read on-policy full review →
02

Side-by-Side Comparison

Field
ir-sim logoir-sim
on-policy logoon-policy
Category
LLM Infra
LLM Infra
Stars
★ 1.2k
★ 2.1k
License
MIT
MIT
Install Command
pip install ir-sim
pip install -e .
Updated
2d ago
2y ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Robotics, Simulator, Python
Multi-Agent Reinforcement Learning, PPO, MAPPO
03

Features

ir-sim logoir-sim
01Simulate diverse robot kinematics, sensors, and behaviors.
02Configure scenarios easily using straightforward YAML files.
03Visualize simulation outcomes with Matplotlib for immediate debugging.
04Support collision detection and customizable behavior policies.
05Suitable for multi-agent/robot reinforcement learning projects.
on-policy logoon-policy
01Implementation of MAPPO (Multi-Agent PPO)
02Support for diverse multi-agent environments (e.g., StarCraft II, Hanabi)
03Ready-to-use training scripts for various scenarios
04Detailed hyperparameter guidance and updated results
05Default support for shared policy among agents
04

Use Cases

ir-sim logoir-sim
↳Simulating multi-robot collision avoidance strategies and group behaviors.
↳Developing and testing robot navigation algorithms in various environments.
↳Prototyping and evaluating deep reinforcement learning models for robotics.
on-policy logoon-policy
↳Research and experimentation in cooperative multi-agent reinforcement learning
↳Benchmarking and evaluating PPO's effectiveness in MARL scenarios
↳Training AI agents for popular multi-agent games like StarCraft II and Hanabi
05

Best For

ir-sim logoir-sim
Trending
on-policy logoon-policy
—
FAQ

FAQ

What is the difference between ir-sim and on-policy?
Both ir-sim and on-policy are in the LLM Infra category. ir-sim has 1.2k stars, while on-policy has 2.1k stars.
Which is better, ir-sim or on-policy?
The best choice depends on your use case. Choose ir-sim if Simulating multi-robot collision avoidance strategies and group behaviors., and on-policy if Research and experimentation in cooperative multi-agent reinforcement learning.
Is ir-sim free or open source?
Yes, ir-sim is open source on GitHub (MIT).
Is on-policy free or open source?
Yes, on-policy is open source on GitHub (MIT).
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Related

Alternatives to ir-sim →Alternatives to on-policy →ir-sim details →on-policy details →