MA-FPPO: Multi-Agent Flow-Pretrained Policy Optimization

arXiv:2609.32594 · cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.AI

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/ma-fppo/MA-FPPO

Project page: https://ma-fppo.github.io

Terminology

• Fine-Tuning — 77× in this paper · explained in 5 episodes
• Actor — 40× in this paper · explained in 3 episodes
• Distillation — 26× in this paper · explained in 2 episodes
• Regularization — 22× in this paper · explained in 3 episodes
• Reinforcement Learning — 21× in this paper · explained in 4 episodes
• KL Regularization — 13× in this paper · explained in 2 episodes
• Flow Matching — 11× in this paper · explained in 8 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Ablation — 9× in this paper · explained in 1 episode
• International Conference on Learning Representations — 7× in this paper
• Q-learning — 7× in this paper · explained in 3 episodes
• Trace — 6× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 5× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Generative Modeling — 2× in this paper · explained in 3 episodes
• One-Step Generative Policy Optimization — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Implicit Constraint Q-learning — 1× in this paper
• Multi-Agent Particle Environments — 1× in this paper
• Multi-Agent Proximal Policy Optimization — 1× in this paper
• Multi-Agent Reinforcement Learning (MARL) — 1× in this paper · explained in 4 episodes
• Multi-agent Batch-Constrained Q-learning — 1× in this paper
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• StarCraft Multi-Agent Challenge — 1× in this paper

Sources

• $\pi_\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
• Proximal Policy Optimization Algorithms
• CoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making

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