{
  "id": 2178,
  "url": "https://www.frontiersin.org/articles/10.3389/frobt.2026.1877762",
  "title": "OpenAI single-agent LLM architecture reduces computational overhead relative to multi-agent orchestration in a simulated mars rover decision-support benchmark",
  "summary": "Mars rover missions require decision-support systems that can interpret terrain, telemetry, environmental conditions, and mission objectives under delayed communication with Earth. This study evaluates whether multi-agent orchestration improves simulated Mars rover decision support compared with a single-agent baseline. A controlled benchmark of 100 synthetic mission-inspired rover scenarios was evaluated using OpenAI GPT-4o and GPT-5.5, with five repeated runs per scenario and architecture. Mod",
  "authors": "Dan Sanabria",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": "openai",
  "regions": null,
  "published_at": "2026-07-06T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "source_slug": "x-frontiers-in-robotics-and-ai",
  "source_name": "Frontiers in Robotics and AI",
  "source_homepage": "https://www.frontiersin.org/journals/robotics-and-ai",
  "ethics_ai_record_url": "https://ethics.ai/record/2178",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frobt.2026.1877762",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}