用大模型辩论达成区块链共识，让每个节点意见都被尊重。
Achieving Unanimous Consensus Through Multi-Agent Deliberation
- 大模型作为理性代理，通过多轮结构化讨论达成一致
- 对确定性问题可实现全体一致共识，对优先级问题支持分级共识
- 适合需要高共识质量的决策场景，如治理、政策制定
区块链共识机制长期依赖工作量证明（PoW）和权益证明（PoS）等算法以保障网络功能与完整性。然而，这些方法在涉及个体意见重要性的决策中表现不佳，难以突破基于诚实多数或加权共识的局限。本文提出一种基于辩论的新型共识机制，其中大语言模型（LLMs）作为理性代理参与结构化讨论，以达成全体一致共识。通过分级共识与多轮辩论流程，该方法在确定性问题上保证全员一致，在优先级决策中支持分级共识。我们形式化了该系统，证明其能维持区块链特性，并分析了对抗行为、辩论停滞及共识置信度等问题。实验表明系统具备可行性，展示了收敛性、区块属性与准确性，为区块链网络上的协商式决策提供了实现路径。
原文摘要 · Abstract (English)
Blockchain consensus mechanisms have relied on algorithms such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) to ensure network functionality and integrity. However, these approaches struggle with adaptability for decision-making where the opinions of each matter rather than reaching an agreement based on honest majority or weighted consensus. This paper introduces a novel deliberation-based consensus mechanism where Large Language Models (LLMs) act as rational agents engaging in structured discussions to reach a unanimous consensus. By leveraging graded consensus and a multi-round deliberation process, our approach ensures unanimous consensus for definitive problems and graded consensus for prioritized decision problems and policies. We provide a formalization of our system and use it to show that the properties of blockchains are maintained, while also addressing the behavior in terms of adversaries, stalled deliberations, and confidence in consensus. Moreover, experimental results demonstrate system feasibility, showcasing convergence, block properties, and accuracy, which enable deliberative decision-making on blockchain networks.
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