title: ProAgent: From Robotic Process Automation to Agentic Process Automation
summary: 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.
paper_authors._id: 655c1bb4419819fec2c0f37c
paper_authors.name: Yining Ye
paper_authors.status: admin_assigned
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paper_authors.avatarUrl: /avatars/331073d0fee901b2b9d93287fabe64fc.svg
paper_authors.fullname: yining ye
paper_authors.type: user
paper_authors.user: yeyn2001
paper_authors._id: 655c1bb4419819fec2c0f37d
paper_authors.name: Xin Cong
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2023-11-21T02:53:41.489Z
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paper_authors.avatarUrl: /avatars/69e34bfa6ce5e9a837e59fb8662e0dab.svg
paper_authors.fullname: Xin Cong
paper_authors.type: user
paper_authors.user: congxin95
paper_authors._id: 655c1bb4419819fec2c0f37e
paper_authors.name: Shizuo Tian
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-11-22T09:48:28.668Z
paper_authors._id: 63ede3b7518f6e69a3572c54
paper_authors.avatarUrl: /avatars/86e3afd3a8344735ef0b186a313bca2c.svg
paper_authors.fullname: Shizuo Tian
paper_authors.type: user
paper_authors.user: BlitherBoom
paper_authors._id: 655c1bb4419819fec2c0f37f
paper_authors.name: Jiannan Cao
paper_authors._id: 655c1bb4419819fec2c0f380
paper_authors.name: Hao Wang
paper_authors._id: 655c1bb4419819fec2c0f381
paper_authors.name: Yujia Qin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-11-21T14:50:14.063Z
paper_authors._id: 643f37cce9d063936912048b
paper_authors.avatarUrl: /avatars/25822ea5676a79b2e1ddf08d5fc2226c.svg
paper_authors.fullname: Yujia Qin
paper_authors.type: user
paper_authors.user: YujiaHi
paper_authors._id: 655c1bb4419819fec2c0f382
paper_authors.name: Yaxi Lu
paper_authors._id: 655c1bb4419819fec2c0f383
paper_authors.name: Heyang Yu
paper_authors._id: 655c1bb4419819fec2c0f384
paper_authors.name: Huadong Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-11-21T14:50:37.285Z
paper_authors._id: 62bb0f41aaa4d91e6459d021
paper_authors.avatarUrl: /avatars/c1d12c99f2d2be1eef02c548d3f13612.svg
paper_authors.fullname: huadong wang
paper_authors.type: user
paper_authors.user: huadw2012
paper_authors._id: 655c1bb4419819fec2c0f385
paper_authors.name: Yankai Lin
paper_authors._id: 655c1bb4419819fec2c0f386
paper_authors.name: Zhiyuan Liu
paper_authors._id: 655c1bb4419819fec2c0f387
paper_authors.name: Maosong Sun
paper_title: ProAgent: From Robotic Process Automation to Agentic Process Automation
paper_summary: 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.
paper_ai_keywords: Large Language Models (LLMs) Agentic Process Automation (APA) LLM-based agents ProAgent workflow construction workflow execution human instructions intricate decisions specialized agents