Revisiting Gossip Protocols: A Vision for Emergent Coordination in Agentic Multi-Agent Systems

• URL: http://arxiv.org/abs/2508.01531v1
• Date: Sun, 03 Aug 2025 01:18:58 GMT
• Title: Revisiting Gossip Protocols: A Vision for Emergent Coordination in Agentic Multi-Agent Systems
• Abstract summary: Gossip protocols offer a missing layer for context-rich, adaptive communication in agentic AI.<n>Gossip enables scalable, low-overhead dissemination of shared knowledge, but also raises unresolved challenges.<n>Gossip is not a silver bullet, but overlooking it risks missing a key path toward resilient, reflexive, and self-organizing multi-agent systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As agentic platforms scale, agents are evolving beyond static roles and fixed toolchains, creating a growing need for flexible, decentralized coordination. Today's structured communication protocols (e.g., direct agent-to-agent messaging) excel at reliability and task delegation, but they fall short in enabling emergent, swarm-like intelligence, where distributed agents continuously learn, adapt, and communicate to form collective cognition. This paper revisits gossip protocols, long valued in distributed systems for their fault tolerance and decentralization, and argues that they offer a missing layer for context-rich, adaptive communication in agentic AI. Gossip enables scalable, low-overhead dissemination of shared knowledge, but also raises unresolved challenges around semantic filtering, staleness, trustworthiness, and consistency in high-stakes environments. Rather than proposing a new framework, this work charts a research agenda for integrating gossip as a complementary substrate alongside structured protocols. We identify critical gaps in current agent-to-agent architectures, highlight where gossip could reshape assumptions about coordination, and outline open questions around intent propagation, knowledge decay, and peer-to-peer trust. Gossip is not a silver bullet, but overlooking it risks missing a key path toward resilient, reflexive, and self-organizing multi-agent systems.

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