Decoupling Correctness from Policy: A Deterministic Causal Structure for Multi-Agent Systems
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915535833268224 |
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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 |
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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 |