这篇论文挖出了智能体共识的一个坑：老实但推理错误的验证器照样能搞砸安全性。用e_δ和u_ε两个指标量化风险，比传统BFT更接地气。搞Agent基础设施的值得一读。
论文提出Honest Quorum Problem，即协议兼容但语义错误的智能体验证器可能满足常规检查而形成无效证书。定义Epistemic Byzantine Fault Tolerance (EBFT)，引入两个置信度索引量e_δ和u_ε，分别约束拜占庭集之外的一致无效认可和降低活跃度的不可用支持。推导了语义有效性、共识一致性、活跃性和阈值选择的充分条件。论证仅当添加名义上不同的智能体能可测量地减少无效认可或不可用支持的尾部分布时，才能提升容错性。
The Honest Quorum Problem: Epistemic Byzantine Fault Tolerance for Agentic Infrastructure
State machine replication (SMR) and Byzantine fault-tolerant (BFT) consensus guarantee agreement despite a bounded number of arbitrary, colluding faulty participants. However, these guarantees rely on participants outside this set correctly executing the protocol's transition semantics. Agentic validators expose a weaker boundary: an authenticated, responsive, non-equivocating, and protocol-compliant reasoning participant may still endorse a semantically invalid transition due to reasoning errors. We call this failure mode an epistemic fault, and the collective phenomenon the Honest Quorum Problem (where "honest" means protocol-compliant, not semantically correct). Such a quorum can satisfy ordinary checks while forming a certificate for an invalid transition. Thus, agreement alone does not guarantee semantic validity or execution safety. Furthermore, because agentic validators often share model weights, training distributions, prompts, or toolchains, they are highly susceptible to correlated epistemic faults. We define Epistemic Byzantine Fault Tolerance (EBFT), a fault-tolerance model for agentic infrastructure and post-deterministic distributed systems. EBFT augments the conventional Byzantine fault bound with two separate, confidence-indexed quantities: $e_δ$ bounds coherent invalid endorsements outside the Byzantine set, and $u_ε$ bounds unusable validator support that degrades liveness. These quantities characterize semantic safety risk and liveness degradation independently. We derive quorum-threshold conditions for semantic validity, consensus agreement, liveness, and feasible threshold selection, and outline a calibration methodology for estimating these budgets. We show that adding nominally distinct agents improves fault tolerance only when it measurably reduces the upper-tail concentration of invalid endorsements or unusable support.