Flowing Faster to Coordinate: One-Step Online Multi-Agent Flow Policies

Excerpt

arXiv:2610.01882v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment. Developing MARL policies requires balancing expressive modeling of complex and multimodal action distributions with efficient training and execution. Generative policies, particularly diffusionbased policies, can faithfully capture complex and multimodal behaviors, but costly iterative sampling hinder