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arXiv

Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure

Title: Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure

Abstract:

Traditional distributed systems have long operated on the premise that reliable nodes strictly adhere to protocol-defined behaviors characterized by stable, externally imposed, and deterministic semantics. While classical theory has deeply explored variables such as communication topologies, network latency, and failure domains, the underlying model of the participating entity has remained largely static. However, the incorporation of autonomous reasoning engines, stochastic model-driven agents, and policy-oriented actors into critical infrastructures—ranging from financial systems and incident response mechanisms to cloud control planes—undermines the universality of this traditional assumption. These modern agents frequently generate unique operational traces, divergent reasoning pathways, and varied internal representations, yet they consistently arrive at semantically identical and correct results.

To address this shift, this paper proposes Post-Deterministic Distributed Systems (PDDS) as a comprehensive research and engineering framework designed to coordinate heterogeneous environments where autonomous agents, stochastic models, and deterministic code operate in concert. We demonstrate that established distributed computing models function as a specific, zero-ambiguity subset of this broader, participant-general model. Our position is not that deterministic systems will vanish; rather, we argue that deterministic execution can no longer be treated as the universal baseline for autonomous infrastructure.

Furthermore, we delineate five core architectural pillars essential for post-deterministic infrastructure: Verifiable Agentic Infrastructure, Protocol-Driven Development, Semantic Quorum Assurance, Autonomous State Control Planes, and Epistemic State Replication. Notably, Epistemic State Replication expands traditional persistence and consistency models by shifting the focus from data visibility to knowledge visibility. This extension facilitates agentic memory, Verifiable Semantic Rollback, and coherence among reasoning participants. The paper also introduces a taxonomy of failure classes specific to this new operational context.


Source: arXiv Generated at: 2026-06-02 00:00:00 UTC

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