ProAgent：從機器人流程自動化到主動式流程自動化

摘要

從古代水車到機器人流程自動化（RPA），自動化技術在歷史上不斷演進，以解放人類免於繁重任務。然而，RPA 在需要類似人類智能的任務上遇到困難，特別是在複雜的工作流程設計和工作流程執行中的動態決策方面。隨著大型語言模型（LLMs）出現具有類似人類智能，本文介紹了主動式流程自動化（APA），這是一種開創性的自動化範式，使用基於LLM的代理人進行先進自動化，將人類勞動轉移給與構建和執行相關的代理人。然後，我們實例化了ProAgent，一個基於LLM的代理人，旨在根據人類指令制定工作流程並通過協調專門代理人做出精細決策。進行了實證實驗以詳細說明其工作流程的構建和執行過程，展示了APA的可行性，揭示了由代理人驅動的新自動化範式的可能性。我們的代碼公開在https://github.com/OpenBMB/ProAgent。

English

From ancient water wheels to robotic process automation (RPA), automation technology has evolved throughout history to liberate human beings from arduous tasks. Yet, RPA struggles with tasks needing human-like intelligence, especially in elaborate design of workflow construction and dynamic decision-making in workflow execution. As Large Language Models (LLMs) have emerged human-like intelligence, this paper introduces Agentic Process Automation (APA), a groundbreaking automation paradigm using LLM-based agents for advanced automation by offloading the human labor to agents associated with construction and execution. We then instantiate ProAgent, an LLM-based agent designed to craft workflows from human instructions and make intricate decisions by coordinating specialized agents. Empirical experiments are conducted to detail its construction and execution procedure of workflow, showcasing the feasibility of APA, unveiling the possibility of a new paradigm of automation driven by agents. Our code is public at https://github.com/OpenBMB/ProAgent.

ProAgent：從機器人流程自動化到主動式流程自動化

ProAgent: From Robotic Process Automation to Agentic Process Automation

摘要

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