verl-agent
★ 1.9k
vs
on-policy
★ 2.0k
verl-agent vs on-policy
verl-agent: `verl-agent` extends veRL to train LLM agents using reinforcement learning, featuring a novel step-independent multi-turn rollout mechanism. This design ensures high scalability for long-horizon tasks by allowing customizable per-step input structures and memory management.; 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 verl-agent if…Training large language model agents for complex multi-turn, long-horizon tasks.
Choose on-policy if…Research and experimentation in cooperative multi-agent reinforcement learning
02
Side-by-Side Comparison
03
Features
verl-agent01Multi-Turn Agent-Environment Interaction
02Fully Customizable Memory Module & Per-Step Input Structure
03Scalable for Very Long-Horizon Optimization
04Parallelized Gym-Style Environments and Group Environments
05Diverse Reinforcement Learning Algorithms
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
verl-agent↳Training large language model agents for complex multi-turn, long-horizon tasks.
↳Developing reasoning agents for both visual and text-based environments.
↳Solving digital interface control, embodied AI, and search-related challenges.
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
verl-agentTrending
on-policyTrendingReinforcement LearningMulti-Agent AI
FAQ
FAQ
What is the difference between verl-agent and on-policy?
Both verl-agent and on-policy are in the Vision / Multimodal category. verl-agent has 1.9k stars, while on-policy has 2.0k stars.
Which is better, verl-agent or on-policy?
The best choice depends on your use case. Choose verl-agent if Training large language model agents for complex multi-turn, long-horizon tasks., and on-policy if Research and experimentation in cooperative multi-agent reinforcement learning.
Is verl-agent free or open source?
Yes, verl-agent is open source on GitHub (Apache-2.0).
Is on-policy free or open source?
Yes, on-policy is open source on GitHub (MIT).
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