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.

翻译：大型语言模型（LLM）促进了自主智能代理的定义。此类代理已在不同领域展现出解决复杂任务的潜力。当它们与其他代理在多代理系统中协作时，其性能可得到进一步提升。然而，这些代理的编排与协调仍具挑战性，尤其是在需要与人类交互的人机协同工作流中。此类工作流需被精确定义，以明确各项任务的负责主体、代理完成个体任务可遵循的策略，或在提出不同备选方案时的决策机制等。现有的业务流程建模语言在描述这类新型混合协同场景时存在不足。本文作为一项探索性研究，对广为人知的流程建模语言（即BPMN）进行了扩展，以支持此类新型工作流的定义。我们的扩展既涵盖了所需新元建模概念的形式化定义，也提出了类BPMN图形化标注方案以简化工作流设计。该扩展已实现并作为开源的人机协同工作流建模编辑器发布于GitHub平台。