Decoupling Correctness from Policy: A Deterministic Causal Structure for Multi-Agent Systems
🤖 AI Summary
In distributed multi-agent systems, correctness is often entangled with operational policies—such as scheduling and batching—making policy evolution prone to violating integrity guarantees. Method: This paper introduces Deterministic Causal Structure (DCS), the first formal framework that decouples correctness from execution policies, establishing a policy-agnostic foundation for correctness. Guided by the asynchronous computation boundary principle, DCS identifies the semilattice structure as a necessary condition for determinism and establishes “correctness-as-infrastructure” as a new paradigm. Contribution/Results: Based on a minimal axiomatized theory, integrating causal modeling and observational equivalence analysis, we rigorously prove four core properties: existence and uniqueness, policy-agnostic invariance, observational equivalence, and axiom minimality. DCS resolves causal ambiguity—unaddressed by existing models such as CRDTs—and enables modular, safe, and evolvable system construction.
Application Category
📝 Abstract
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.
Problem
Research questions and friction points this paper is trying to address.
Decouples correctness from operational policies in multi-agent systems
Resolves causal ambiguities that value-centric convergence models cannot address
Establishes correctness as a fixed policy-agnostic substrate for distributed systems
Innovation
Methods, ideas, or system contributions that make the work stand out.
Decouples correctness from operational policies
Establishes deterministic causal structure axioms
Uses join-semilattice for policy-agnostic guarantees
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