arXiv AI
Composition without a Host: Carrying the Spatiotemporal-Composability Guarantee of Plugin-Based Agents across Processes
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arXiv AI
Sep 1
Logos: An Agent Harness on a Cross-Process Bus
arXiv:2608.28553v2 Announce Type: replace Abstract: Modern agent systems assemble capabilities at runtime, and this dynamic composition has recently received a complete formal treat ment in the spati...
arXiv AI
Sep 2
Runtime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers
arXiv:2609. 00546v1 Announce Type: cross Abstract: Agent systems are commonly described by the model and harness that currently produce their behavior.
arXiv AI
Jul 8
Proof of Execution: Runtime Verification for Governed AI Agent Actions
arXiv:2607. 05397v1 Announce Type: cross Abstract: Agent systems increasingly execute rather than advise.
arXiv AI
Aug 28
Agent Mesh: Reliability Primitives for Non-Idempotent Agent Delegation - Identity Adequacy and Evidence Adequacy
The paper reports a failure study of a production agentic software‑delivery platform, analyzing 147 incidents across 81 runs. It shows that the standard reliability primitives—retry, timeout, and error‑rate circuit breaking—fail in practice, leading to costly loops, false trips, and blocked work. The authors identify two cross‑cutting causes—identity adequacy and evidence adequacy—and propose seven new reliability primitives that enforce reliability at the delegation level.
arXiv AI
3d ago
FAOPs: Normal Forms and an Algebra for AI Agent Workflows
FAOPs introduces a formal framework for AI agent workflows, called Functional Agent Operating Procedures, that applies database‑grade discipline to multi‑step agent skills. It normalizes workflows into four progressive normal forms—Decomposed, Typed, Factored, and Scoped—ensuring each atomic step is type‑checked, scoped, bounded, and auditable. The framework includes a provably sound algebra for refactoring and parallelization, extensions for verified termination, optimization, and cost bounds, and an architectural classifier to assess AI necessity, all implemented in the SkillBase system with a runtime executor.
arXiv Machine Learning
Aug 5
Resume Means Resume: A Machine-Checked Conformance Contract for Checkpoint, Interrupt, and Resume Semantics in Workflow Persistence Layers
arXiv:2608. 03836v1 Announce Type: new Abstract: A framework that persists execution state so a run can be interrupted, survive a crash, and continue must decide what a resume means for effects that already fired.