Auditing Action Settlement in LLM Agent Environments: Order, Progress, and Replay

2026-10-01

AI Summary

This study addresses the challenge of arbitrating concurrent actions among LLM agents by proposing a joint strategy based on typed snapshot settlement contracts. Methodologically, it introduces a space-order-invariant proposal mechanism and conducts full-state log auditing through exhaustive permutation trials and multi-step episode simulations to evaluate order sensitivity, valid progress, and replay consistency. Experimental results demonstrate that a randomized ticket strategy improves task completion rates by 59.03% over a conservative rejection baseline. Furthermore, the approach successfully replays 156 checkpoints while intercepting 1,332 constructed errors, thereby achieving highly reliable concurrent execution alongside precise corruption rejection.

Abstract

Concurrent actions in large language model (LLM) agent environments require arbitration even when each proposal is individually valid. We implement a typed snapshot-settlement contract and audit three distinct properties: order sensitivity, useful progress, and replay consistency. Five settlement policies are tested in 28,800 exhaustive permutation trials and 2,160 scripted multistep episodes. Joint policies are spatially order-invariant conditional on fixed priorities, yet conservative rejection completes only 31.25% of agents in a six-agent doorway task versus 90.28% for random tickets; the paired improvement is 59.03 percentage points (95% bootstrap interval: 50.00-68.06). All policies preserve the tested spatial constraints, and priority arbitration still misses the independent small-instance optimum. A separate full-state journal audit exactly replays 156 checkpoints and rejects 1,332 constructed corruptions with a retained terminal anchor. The evidence concerns execution semantics, not human realism or long-run fairness.

Problem

• LLM agent environments
• concurrent actions
• action settlement
• arbitration
• replay consistency

Innovation

• LLM Agent Environments
• Snapshot-Settlement Contract
• Concurrent Action Arbitration
• Replay Consistency
• Settlement Policies