提出后确定性系统模型,应对智能体共存下的可信自治基础设施挑战
Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure
- 用后确定性模型统一协调确定性代码与随机智能体的协同
- 定义五项架构支柱,实现知识可见性与可验证回滚
- 适合研究自治系统、云控制平面与金融基础设施的学者
长期以来,分布式系统假设正确参与者以稳定、外定且确定性的语义执行协议行为。经典理论虽细致参数化了网络时延、通信拓扑和故障域,但对参与者的假设始终未变。如今,自主推理引擎、随机模型驱动的智能体与策略驱动的实体被集成至云控制平面、事件响应系统及金融基础设施中,挑战了这一假设的普适性。这些智能体在达成语义等价正确结果的同时,常产生分歧的推理路径、不同的操作轨迹和异构的内部表示。本文提出后确定性分布式系统(PDDS)作为研究与工程模型,用于协调确定性代码、随机模型与自治智能体共存的异构环境。我们证明经典分布式计算模型是此通用参与者模型的零歧义特例。并非否定确定性系统,而是指出确定性执行已无法作为自治基础设施的普遍参与者假设。最后,我们提出后确定性基础设施的五大架构支柱:协议驱动开发、可验证智能体基础设施、自治状态控制平面、语义多数保证与认知状态复制。认知状态复制将持久性与一致性模型从数据可见性扩展至知识可见性,支持智能体记忆、可验证语义回滚及推理参与者间的一致性。我们还定义了该场景下的失败类型分类体系。
原文摘要 · Abstract (English)
For decades, distributed systems have typically assumed that correct participants execute protocol-specified behavior with stable, externally defined, and deterministic semantics. Classical theory has extensively parameterized network timing, communication topologies, and failure domains, but this participant model has remained comparatively fixed. The integration of autonomous reasoning engines, stochastic model-driven agents, and policy-driven actors into cloud control planes, incident response systems, and financial infrastructure challenges the universality of this assumption. These agents often produce divergent reasoning paths, distinct operational traces, and heterogeneous internal representations while achieving semantically equivalent and correct outcomes. In this paper, we introduce Post-Deterministic Distributed Systems (PDDS) as a research and engineering model for coordinating heterogeneous environments where deterministic code, stochastic models, and autonomous agents coexist. We show that classical distributed computing models form a zero-ambiguity special case of this participant-general model. We do not argue that deterministic systems disappear; rather, deterministic execution can no longer serve as the universal participant assumption for autonomous infrastructure. Finally, we outline five architectural pillars of post-deterministic infrastructure: Protocol-Driven Development, Verifiable Agentic Infrastructure, Autonomous State Control Planes, Semantic Quorum Assurance, and Epistemic State Replication. Epistemic State Replication extends persistence and consistency models from data visibility to knowledge visibility, enabling agentic memory, Verifiable Semantic Rollback, and coherence across reasoning participants. We also define a taxonomy of failure classes that arise in this setting.
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