用形式化框架让智能体在流程中自主决策更可靠。
A Formal Framework for Declarative Agentic AI in Business Process Analysis
- 提出AGO方法：从代理、目标、对象三方面建模业务流程
- 构建可查询、可更新的业务流程知识库，确保路径完整正确
- 适合需要高可靠性的自动化流程设计与分析场景
智能体人工智能为自动化业务流程带来新机遇，实现自主决策与动态适应。但要发挥其潜力，必须对流程实体及其交互进行形式化定义。本文提出基于AGO方法的形式化框架，通过代理（Agents）、目标（Goals）和对象（Objects）三个维度刻画建模视角。基于集合论与数学逻辑，我们正式定义了AGO实体类型及其交互关系，并将所有定义组织成业务流程知识库（BPKB）。该知识库支持结构化查询、增量更新以及自动化的流程工作流生成，同时保证所推导路径的合理性与完备性。
原文摘要 · Abstract (English)
Agentic AI opens new opportunities for automating Business Process (BP), enabling autonomous decision-making and dynamic adaptation. However, realising this potential requires BP entities and their interactions to be defined with formal precision. This paper presents a formal framework for Agentic BP analysis through the AGO methodology. AGO captures the modelling perspective in terms of who is acting (Agents), why it is carried out (Goals), and what the relevant entities are (Objects). Grounded in set theory and mathematical logic, we formally define the AGO entity types and their interactions, organising all definitions into a BP Knowledge Base (BPKB). The resulting BPKB supports structured querying, incremental updates, and automatic generation of BP workflows, while ensuring soundness and completeness of the derived paths.
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