Decoupling Correctness from Policy: A Deterministic Causal Structure for Multi-Agent Systems

Fuente: arXiv
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Main Authors: Ren, Zhiyuan, Zhang, Tao, Chen, Wenchi
Format: Preprint
Published: 2025
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author Ren, Zhiyuan
Zhang, Tao
Chen, Wenchi
author_facet Ren, Zhiyuan
Zhang, Tao
Chen, Wenchi
contents In distributed multi-agent systems, correctness is often entangled with operational policies such as scheduling, batching, or routing, which makes systems brittle since performance-driven policy evolution may break integrity guarantees. This paper introduces the Deterministic Causal Structure (DCS), a formal foundation that decouples correctness from policy. We develop a minimal axiomatic theory and prove four results: existence and uniqueness, policy-agnostic invariance, observational equivalence, and axiom minimality. These results show that DCS resolves causal ambiguities that value-centric convergence models such as CRDTs cannot address, and that removing any axiom collapses determinism into ambiguity. DCS thus emerges as a boundary principle of asynchronous computation, analogous to CAP and FLP: correctness is preserved only within the expressive power of a join-semilattice. All guarantees are established by axioms and proofs, with only minimal illustrative constructions included to aid intuition. This work establishes correctness as a fixed, policy-agnostic substrate, a Correctness-as-a-Chassis paradigm, on which distributed intelligent systems can be built modularly, safely, and evolvably.
format Preprint
id arxiv_https___arxiv_org_abs_2510_05621
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Decoupling Correctness from Policy: A Deterministic Causal Structure for Multi-Agent Systems
Ren, Zhiyuan
Zhang, Tao
Chen, Wenchi
Distributed, Parallel, and Cluster Computing
Multiagent Systems
In distributed multi-agent systems, correctness is often entangled with operational policies such as scheduling, batching, or routing, which makes systems brittle since performance-driven policy evolution may break integrity guarantees. This paper introduces the Deterministic Causal Structure (DCS), a formal foundation that decouples correctness from policy. We develop a minimal axiomatic theory and prove four results: existence and uniqueness, policy-agnostic invariance, observational equivalence, and axiom minimality. These results show that DCS resolves causal ambiguities that value-centric convergence models such as CRDTs cannot address, and that removing any axiom collapses determinism into ambiguity. DCS thus emerges as a boundary principle of asynchronous computation, analogous to CAP and FLP: correctness is preserved only within the expressive power of a join-semilattice. All guarantees are established by axioms and proofs, with only minimal illustrative constructions included to aid intuition. This work establishes correctness as a fixed, policy-agnostic substrate, a Correctness-as-a-Chassis paradigm, on which distributed intelligent systems can be built modularly, safely, and evolvably.
title Decoupling Correctness from Policy: A Deterministic Causal Structure for Multi-Agent Systems
topic Distributed, Parallel, and Cluster Computing
Multiagent Systems
url https://arxiv.org/abs/2510.05621