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.

翻译：区块链共识机制一直依赖工作量证明（PoW）和权益证明（PoS）等算法来确保网络功能与完整性。然而，在需要重视每个参与者意见而非基于诚实多数或加权共识达成一致的决策场景中，这些方法难以适应。本文提出一种基于审议的新型共识机制，其中大型语言模型（LLM）作为理性智能体参与结构化讨论，以达成一致共识。通过利用分级共识与多轮审议流程，我们的方法能够为确定性问题实现一致共识，并为优先级决策问题及策略实现分级共识。我们给出了系统的形式化描述，并以此证明区块链特性得以保持，同时针对对抗行为、审议停滞及共识置信度等问题进行了分析。此外，实验结果验证了系统的可行性，展示了收敛性、区块特性与准确性，从而实现了区块链网络上的审议式决策。