When AI Agents Commit: Cognitive Serializability Across Data, Evidence, Policy, and Authority
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Abstract (arXiv)
Autonomous agents derive concrete mutations from database reads, retrieved evidence, policy, beliefs, and delegated authority. Those inputs may change while reasoning is in progress. Database isolation orders the submitted transaction; agentic transaction processing determines whether a proposal satisfies an executable contract. Neither guarantee establishes a common valid point for the mutation and its derivation inputs unless the contract represents the relevant predicates. Typed dependency tokens distinguish content integrity from applicability, and trusted mediation captures the values exposed to reasoning. Under strict Cognitive Serializability, committed effects admit a serial order and a logical event at which every value exposed to derivation is unchanged. The fences last until the runtime event that realizes the sealed durability domain. The weaker Effect-Compatible Cognitive Admission recertifies an effect against a simultaneously held current dependency vector and current policy without claiming to serialize the original stochastic derivation. TCT combines immutable versioned executable definitions, registry-derived authority plans, sealed envelopes, guard-first commit transactions, post-seal envelope- and witness-bound grants, co-committed receipts, idempotent grant finalization, and receipt-driven epistemic reconciliation. Complete registered footprints and a single growing phase induce an acyclic lock-point order over local guards and incompatible external reservations. The corresponding results give serializability conditions and an observational-equivalence boundary for zero-error soundness and positive progress. A falsification suite tests the implementation obligations: the prototype prevented all injected anomalies and added 3.22 ms mean commit overhead.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 38 references that are in the map. First posted on arXiv 28 Jul 2026.
Builds on
8 of 38 references.
References · 8
- 2025SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planningcited by 58
- 2026Atomix: Timely, Transactional Tool Use for Reliable Agentic Workflowscited by 27
- 2026Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agentscited by 17
- 2026S-Bus: Automatic Read-Set Reconstruction for Multi-Agent LLM State Coordinationcited by 8
- 2026Mnemosyne: Agentic Transaction Processing for Validating and Repairing AI-generated Workflowscited by 8
- 2026CoAgent: Concurrency Control for Multi-Agent Systemscited by 4
- 2026ATCC: Adaptive Concurrency Control for Unforeseen Agentic Transactionscited by 3
- 2026Replicating Belief, Not Bits: Epistemic State Replication for Agentic Systemscited by 1
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Citing papers per year: 2026: 1.
1 paper.
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- 2026MemTX: Transactional Belief Commit for Stateful Agent Memory
- 2026TRACE: An Operational Reasoning Schema for Auditable Agentic Commitments
- 2026The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents
- 2026Cognitive Admission Control: Risk-Conditioned Assurance for Consequential Actions in Agentic Distributed Systems
- 2026Correct Is Not Governed: Provenance Integrity in Agentic Workflows
- 2026When Stale Constraints Go Unchecked: Budgeted Verification Failures in Inherited Agent Memory
- 2026Stored Is Not Supported: Typed Provenance and Assertion Guardrails for Persistent AI Agents
- 2026Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift