Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension

TL;DR

This paper introduces an extension to BPMN to better model human-agentic collaborative workflows, addressing current limitations in specifying responsibilities, strategies, and decision-making in mixed human-agent systems.

Contribution

It provides a formalized extension to BPMN with a new metamodel and graphical notation, enabling precise modeling of human-agent collaborative workflows.

Findings

Extended BPMN supports human-agent collaboration modeling.

Implemented as an open-source editor on GitHub.

Facilitates clear responsibility and decision specification in workflows.

Abstract

Large Language Models (LLMs) have facilitated the definition of autonomous intelligent agents. Such agents have already demonstrated their potential in solving complex tasks in different domains. And they can further increase their performance when collaborating with other agents in a multi-agent system. However, the orchestration and coordination of these agents is still challenging, especially when they need to interact with humans as part of human-agentic collaborative workflows. These kinds of workflows need to be precisely specified so that it is clear whose responsible for each task, what strategies agents can follow to complete individual tasks or how decisions will be taken when different alternatives are proposed, among others. Current business process modeling languages fall short when it comes to specifying these new mixed collaborative scenarios. In this exploratory paper, we extend a well-known process modeling language (i.e., BPMN) to enable the definition of this new type of workflow. Our extension covers both the formalization of the new metamodeling concepts required and the proposal of a BPMN-like graphical notation to facilitate the definition of these workflows. Our extension has been implemented and is available as an open-source human-agentic workflow modeling editor on GitHub.