发表机构
City University of Hong Kong（香港城市大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出PACE系统，通过测量编译回报和在线决策算法，在GUI代理重复任务中实现令牌成本降低17%-25%，并保证总成本不超过代理运行成本的1+ε倍。
AI 中文摘要
将代理重复执行的GUI程序编译成程序可以降低其令牌成本。然而，衡量回报和决定何时编译面临两个挑战。首先，编译成本是不确定的，因为尝试可能需要修复，并且仍然可能无法生成可用的程序。其次，未来重用是未知的，因为任务可能停止到达，或者GUI漂移可能导致程序停止工作。为了解决这些挑战，我们提出了PACE（回报感知的从经验编译），一个具有测量协议和在线编译算法的系统。测量协议记录成功和失败的编译成本，并在匹配的任务输入上比较代理和程序执行成本，以估计每次使用的节省和回报次数。利用这些测量，在线算法根据过去的任务到达和编译结果，将估计的未来节省与编译成本（包括失败的尝试）进行比较。它在允许任一操作之前，根据观察到的任务到达确定的累计预算检查执行和编译费用。在所述行动成本假设下，每次到达后的总成本最多为使用代理运行每个任务成本的$1+\u03b5$倍。对于成功的编译尝试，估计的回报次数（不包括源代理运行）为2-16次使用。在使用记录的任务到达的模拟中，PACE平均将令牌成本降低17.3%（与ReAct相比），24.9%（与AutoRPA改编相比），以及17.3%（与ToolPro改编相比）（$\u03b5=0.25$）。
英文摘要
Compiling GUI procedures that agents execute repeatedly into programs can reduce their token costs. However, measuring payback and deciding when to compile have two challenges. First, compilation costs are uncertain because attempts can require repair and still fail to produce a usable program. Second, future reuse is unknown because tasks may stop arriving or GUI drift may stop the program from working. To address these challenges, we propose PACE (Payback-Aware Compilation from Experience), a system with a measurement protocol and an online compilation algorithm. The measurement protocol records successful and failed compilation costs, and compares agent and program execution costs on matched task inputs to estimate per-use savings and payback counts. Using these measurements, the online algorithm compares estimated future savings with compilation costs, including failed attempts, based on past task arrivals and compilation outcomes. It checks execution and compilation charges against a cumulative budget determined by observed task arrivals before allowing either action. Under stated action-cost assumptions, total cost after each arrival is at most $1+ε$ times the cost of running every task with the agent. For successful compilation attempts, estimated payback counts excluding source agent runs are 2-16 uses. In simulations using recorded task arrivals, PACE reduces token costs by 17.3% compared with ReAct, 24.9% with the AutoRPA adaptation, and 17.3% with the ToolPro adaptation on average ($ε=0.25$).
Comments27 pages, 3 figures
