Pnyx: Robust Communication and Dynamic Authority for Collaborative VLA Agents

Vision-language-action (VLA) models provide a language-conditioned interface between visual reasoning and closed-loop control, but are typically deployed as egocentric policies without mechanisms for sharing observations, distributing subtasks, or scheduling around task conflicts. To demonstrate the benefit of collaborative VLA agents, we study VLA-driven multi-agent systems (VLA-MAS), augmenting the conventional dual-system VLM and action expert pairing with a collaborative layer operating between user prompting and the model's existing natural-language interface. To support decentralized coordination, we introduce a novel system, PNYX, combining a structured, fault-tolerant communication protocol with dynamic task leadership. The protocol tracks message purpose, freshness, receipt, and agreement, while the leader-based architecture temporarily centralizes proposal formation and preserves local review, execution, and fallback. We evaluate PNYX across six closed-loop cooperative-driving tasks and show improvement in nominal joint success from 51.2% for the strongest canonical baseline to 58.3%, while increasing route completion from 75.9% to 80.7%. Under severely degraded communication, PNYX reaches 55.4% joint success, compared with 42.5% for centralized and 53.8% for free-form decentralized planning. Our work highlights that effective VLA collaboration depends not only on communication volume, but also on explicit commitment and network-aware adaptation in information and decision authority.