aiqbench analysis
This research introduces Causal Past Logic (CPL) to enable rigorous runtime verification of distributed LLM agent workflows, addressing the challenge of asynchronous event visibility across lifelines. By extending the ZipperGen framework with guards that inspect causally visible events from other agents, the study ensures local monitor values align with global denotational semantics without requiring centralized state. This advancement is critical for building reliable, verifiable multi-agent systems where decisions must depend strictly on currently known information.
Causal Past Logic for Runtime Verification of Distributed LLM Agent Workflows
arXiv:2605.20923v2 Announce Type: replace-cross Abstract: We study runtime monitoring for distributed LLM-agent workflows. In an asynchronous execution, a decision can only depend on events that are causally visible to the lifeline that makes it: an event that appears earlier in some log may still be unknown locally. We extend the ZipperGen agent-workflow framework with Causal Past Logic (CPL), an adaptation of PT-DTL to guards in if-constructs and while loops. In addition to standard past-time modalities such as previous and since, a guard can inspect the latest causally visible event of another lifeline and selected variables stored there. The owner evaluates the guard online to select the next branch or loop step. We adapt the knowledge-vector monitor to ZipperGen and prove that the locally computed monitor value coincides with the denotational semantics of the guard at the current event.
Abstract:We study runtime monitoring for distributed LLM-agent workflows. In an asynchronous execution, a decision can only depend on events that are causally visible to the lifeline that makes it: an event that appears earlier in some log may still be unknown locally. We extend the ZipperGen agent-workflow framework with Causal Past Logic (CPL), an adaptation of PT-DTL to guards in if-constructs and while loops. In addition to standard past-time modalities such as previous and since, a guard can inspect the latest causally visible event of another lifeline and selected variables stored there. The owner evaluates the guard online to select the next branch or loop step. We adapt the knowledge-vector monitor to ZipperGen and prove that the locally computed monitor value coincides with the denotational semantics of the guard at the current event.
21 pages. Accepted at ICFEM 2026. Camera-ready revision: CPL positioned as an adaptation of PT-DTL, with revised related work and an expanded implementation and preliminary evaluation section
Logic in Computer Science (cs.LO); Artificial Intelligence (cs.AI); Programming Languages (cs.PL)
arXiv:2605.20923 [cs.LO]
(or arXiv:2605.20923v2 [cs.LO] for this version)
Full text under the publisher's open licence · 179 words
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