Clément Burgelin, Rachid Guerraoui, Zicong Hong, Yinan Hu, Anne-Marie Kermarrec, Rafael Pires, Rasmus Moorits Veski, Martijn de Vos · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30114 · open-access PDF
Consensus는 분산 컴퓨팅에서 근본적인 문제이며 상태 기계 복제 (SMR)의 핵심입니다. 수십 년간의 적극적인 인간 연구에도 불구하고, 프로토콜 지식, 정확성 추론, 구현 및 실험 평가를 결합해야하기 때문에 문제에 대한 실용적인 낮은 지연 솔루션을 발견하는 것은 여전히 열려 있습니다. 우리는 AI가 A-greement, 지리적으로 복제 된 상태 기계를위한 새로운 합의 프로토콜을 발견하는 데 어떻게 도움을 주었는지 보고합니다.
Machine translation (Meta M2M100); the English original follows.
Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR). Despite decades of active human research, discovering practical low-latency solutions to the problem is still open, as it requires combining protocol knowledge, correctness reasoning, implementation, and experimental evaluation. We report on how AI helped us discover A-greement, a new consensus protocol for geo-replicated state machines that significantly outperforms state-of-the-art solutions. Averaged across six deployments with 5 or 9 replicas, A-greement reduces the mean latency
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