arXiv AI By Genliang Zhu, Chu Wang

Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation

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The paper introduces a fault‑tolerant budget conservation framework for distributed multi‑agent delegation, where budgets are represented as exclusive escrow credits that traverse a delegation DAG. It details how each branch converts credit into a reservation tied to lineage, epoch, and idempotency, persists a signed dispatch permit, and ensures that uncertain effects remain charged until settlement or retirement. The authors prove properties such as ownership partition, ledger conservation, and at‑most‑once settlement, and validate the mechanism through TLA+ checks, a JavaScript explorer, and crash‑injected SQLite experiments.

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arXiv AI
2d ago

Authorization for Self-Modifying AI Agent Populations: Conserving Authority across Replacement, Forking, and Rollback

The paper introduces "authorization succession," a framework that preserves authority across self‑modifying AI agent populations that can replace, fork, or roll back. It defines a protocol binding each generation to a manifest, root, unique parent, lineage, and population sequence, and establishes invariants that control root‑lifetime consumption and population exposure. The authors prove properties such as population‑safe succession, fork conservation, and rollback non‑reminting, and validate the approach with an executable evaluation covering 32 decisions and external adapters for two mutation systems.

By Genliang Zhu, Chu Wang
arXiv AI
Sep 15

AcquireBound: Runtime Authorization for Resources Acquired by AI Agents

AcquireBound is a runtime authorization framework that ensures AI agents can safely acquire and activate resources such as compute, credentials, and services. It quarantines acquired outputs, resolves their capabilities through authenticated evidence, and activates them only after verifying a manifest, provenance, and relational constraints. The system demonstrates strong safety properties, passing extensive benign and unsafe trace tests across multiple resource classes.

By Genliang Zhu