A Formal Framework for Declarative Agentic AI in Business Process Analysis
arXiv AIArchived Jun 16, 2026✓ Full text saved
arXiv:2606.15291v1 Announce Type: new Abstract: 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 wh
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Computer Science > Artificial Intelligence
[Submitted on 13 Jun 2026]
A Formal Framework for Declarative Agentic AI in Business Process Analysis
Mohammad Azarijafari, Luisa Mich, Michele Missikoff
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.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2606.15291 [cs.AI]
(or arXiv:2606.15291v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2606.15291
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Submission history
From: Mohammad Azarijafari [view email]
[v1] Sat, 13 Jun 2026 13:12:16 UTC (197 KB)
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