{"slug": "consensus-within-competition-between-decentralized-llm-teams-for-perimeter", "title": "Consensus Within, Competition Between: Decentralized LLM Teams for Perimeter Defense", "summary": "A decentralized LLM team using an auction-based consensus protocol breached a simulated perimeter 15% of the time, versus 32% for a single central commander and 29% for independent agents, according to an arXiv paper (2610.41044v1) from the Kas Lab. The study found that only limited radio range among five network conditions changed a team's breach rate, raising the commander's, and that giving a low-cost LLM more authority over bid computation raised consensus-team breaches by 38 percentage points. When intruders disguised themselves as existing taxidermy bird drones, both low-cost and near-frontier LLMs went unpursued in 59-61% of near-frontier decisions (1-16% before), but a one-sentence forewarning in the prompt lowered that to 0-25%.", "body_md": "arXiv:2610.41044v1 Announce Type: new \nAbstract: The use of large language models (LLMs) to coordinate multi-agent teams raises a fundamental architectural question: whether task allocation should be centralized in a single LLM controller or distributed across autonomous LLM agents, particularly when communication is unreliable. In a deliberately simplified perimeter-defense simulation against LLM-controlled intruders, we compared a central commander, an auction-based consensus team and independent agents under five network conditions. Breach rates were 15% for the consensus team, 32% for the commander and 29% for independent agents, and of the different network conditions, only limited radio range changed a team's breach rate, raising the commander's. In consensus team, giving a low-cost LLM more authority over the bid computation raised breaches by 38 percentage points. With birds and civilian drones in airspace, we added a photograph for each to the input text state. Only the near-frontier model treated them apart from intruders. Intruders disguised as existing taxidermy bird drones were mistook as birds by both low-cost and near-frontier LLMs, going unpursued in 59-61% of near-frontier decisions (1-16% before). However, a one-sentence forewarning in the prompt lowered it to 0-25%. We find that LLM team with a dedicated external conflict resolution protocol results in fewest breaches. Code: https://github.com/the-kas-lab/consensus-within-competition-between.", "url": "https://wpnews.pro/news/consensus-within-competition-between-decentralized-llm-teams-for-perimeter", "canonical_source": "https://arxiv.org/abs/2610.41044", "published_at": "2026-11-02 05:00:00+00:00", "updated_at": "2026-11-03 05:21:00.381725+00:00", "lang": "en", "topics": ["ai-agents", "large-language-models", "ai-research", "ai-safety"], "entities": ["Kas Lab", "arXiv"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/consensus-within-competition-between-decentralized-llm-teams-for-perimeter", "markdown": "https://wpnews.pro/news/consensus-within-competition-between-decentralized-llm-teams-for-perimeter.md", "text": "https://wpnews.pro/news/consensus-within-competition-between-decentralized-llm-teams-for-perimeter.txt", "jsonld": "https://wpnews.pro/news/consensus-within-competition-between-decentralized-llm-teams-for-perimeter.jsonld"}}