ir-sim
★ 1.1k
vs
on-policy
★ 2.0k
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
Choose ir-sim if…Simulating multi-robot collision avoidance strategies and group behaviors.
Choose on-policy if…Research and experimentation in cooperative multi-agent reinforcement learning
02
Side-by-Side Comparison
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Features
ir-sim01Simulate 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-policy01Implementation 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↳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↳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-simTrending
on-policyTrendingReinforcement LearningMulti-Agent AI
FAQ
FAQ
What is the difference between ir-sim and on-policy?
Both ir-sim and on-policy are in the Vision / Multimodal category. ir-sim has 1.1k stars, while on-policy has 2.0k 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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