On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery
- URL: http://arxiv.org/abs/2604.22455v1
- Date: Fri, 24 Apr 2026 11:20:25 GMT
- Title: On the Hybrid Nature of ABPMS Process Frames and its Implications on Automated Process Discovery
- Abstract summary: A core component of any AI-Augmented Business Process Management System (ABPMS) is the process frame.<n>In this paper, we conceptualize the notion of an ABPMS process frame as a hybrid business process representation, consisting of semi-concurrently executed procedural and declarative process models.
- Score: 10.74252380914441
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A core component of any AI-Augmented Business Process Management System (ABPMS) is the process frame, which gives the system process-awareness and defines the boundaries in which the system must operate. Compared to traditional process models, the process frame should, in principle, provide a somewhat more permissive representation of the managed processes, such that the (semi) autonomous behavior of an ABPMS, referred to as framed autonomy, could emerge. At the same time, it is not limited to a single linguistic or symbolic formalism and may incorporate heterogeneous knowledge ranging from predefined procedures to commonsense rules and best practices. In this paper, we conceptualize the notion of an ABPMS process frame as a hybrid business process representation, consisting of semi-concurrently executed procedural and declarative process models. We rely on our earlier works to outline the execution semantics of this type of process frame, arguing in favor of adopting the open-world assumption of the declarative paradigm also for procedural process models. The latter leads to a constraint-like interpretation, where each procedural model is considered to constrain the activities within that model, without imposing explicit execution requirements nor limitations on activities that may be present in other models. This is analogous to existing declarative languages, such as Declare, where each constraint has a direct effect only on the specific activities being constrained. Given this similarity, we propose mapping subsets of discovered declarative constraints into equivalent semi-concurrently executed procedural fragments, thus laying the foundation for a corresponding process (frame) discovery approach.
Related papers
- Contrastive Energy Fields for Inference-Time Procedure Planning in Instructional Videos [48.22554718706414]
We propose CEFITO, a procedure planning approach that learns a predictor to express an action-conditioned representation space.<n>Unlike prior methods, CEFITO explicitly reasons over the action space by omitting irrelevant actions during inference-time planning.
arXiv Detail & Related papers (2026-08-17T11:56:11Z) - Multiparty Session Types for GDPR Purpose Compliance [0.0]
We introduce a formal, purpose-aware framework for distributed systems.<n>Within our framework, system implementations are specified using a calculus that captures the semantics of distributed interactions and features private data as a first-class entity.
arXiv Detail & Related papers (2026-07-22T14:15:41Z) - Supporting Autonomous Process Execution within a Multi-Perspective Constraint Frame via Numeric Planning [2.8555387714154485]
Framed Autonomy denotes the capability of a system to autonomously advance the execution of a Business Process (BP) instance.<n>We introduce a novel tool for what-if analysis that augments the process frame with multi-perspective constraints.<n>Given a partial process execution, the proposed approach exploits this enriched frame to recommend optimal continuations in compliance with the underlying process specifications.
arXiv Detail & Related papers (2026-07-18T09:58:35Z) - Modeling and Simulation Based Engineering in the Context of Cyber-Physical Systems [51.82266520875928]
Execution semantics are not treated as first-class engineering entities.<n>Modeling and Simulation Based Engineering organizes engineering around an iterative cycle alternating formal execution, experimental execution, verification, and activity-mediated validation.<n>These applications show that the framework generalizes beyond CPS to any system whose behavior depends on explicitly defined execution conditions.
arXiv Detail & Related papers (2026-04-13T12:42:12Z) - Executable Ontologies in Game Development: From Algorithmic Control to Semantic World Modeling [51.56484100374058]
We argue that Executable Ontologies (EO) represent a transition from algorithmic behavior programming to semantic world modeling.<n>We show how EO achieves prioritybased task interruption through dataflow conditions rather than explicit preemption logic.
arXiv Detail & Related papers (2026-01-12T19:57:35Z) - Direct Encoding of Declare Constraints in ASP [9.599644507730106]
We introduce a novel encoding for Declare constraints that directly models their semantics as ASP rules.<n>We assess the effectiveness of this novel approach on two Process Mining tasks.
arXiv Detail & Related papers (2024-12-13T14:11:33Z) - AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation [6.590869939300887]
Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios.
This paper introduces AgentSimulator, a resource-first BPS approach that discovers a multi-agent system from an event log.
Our experiments show that AgentSimulator achieves computation state-of-the-art simulation accuracy with significantly lower times than existing approaches.
arXiv Detail & Related papers (2024-08-16T07:19:11Z) - A Step Towards a Universal Method for Modeling and Implementing Cross-Organizational Business Processes [0.0]
This study lays the groundwork for more accurate and unified business process model executions.
It describes the development of a prototype translator that converts specific BPMN elements into a format compatible with PASS.
These models are then transformed into source code and executed in a bespoke workflow environment.
arXiv Detail & Related papers (2024-06-18T06:19:44Z) - Process Modeling With Large Language Models [42.0652924091318]
This paper explores the integration of Large Language Models (LLMs) into process modeling.
We propose a framework that leverages LLMs for the automated generation and iterative refinement of process models.
Preliminary results demonstrate the framework's ability to streamline process modeling tasks.
arXiv Detail & Related papers (2024-03-12T11:27:47Z) - FRAPPE: A Group Fairness Framework for Post-Processing Everything [48.57876348370417]
We propose a framework that turns any regularized in-processing method into a post-processing approach.
We show theoretically and through experiments that our framework preserves the good fairness-error trade-offs achieved with in-processing.
arXiv Detail & Related papers (2023-12-05T09:09:21Z) - Code Models are Zero-shot Precondition Reasoners [83.8561159080672]
We use code representations to reason about action preconditions for sequential decision making tasks.
We propose a precondition-aware action sampling strategy that ensures actions predicted by a policy are consistent with preconditions.
arXiv Detail & Related papers (2023-11-16T06:19:27Z) - Relational Action Bases: Formalization, Effective Safety Verification,
and Invariants (Extended Version) [67.99023219822564]
We introduce the general framework of relational action bases (RABs)
RABs generalize existing models by lifting both restrictions.
We demonstrate the effectiveness of this approach on a benchmark of data-aware business processes.
arXiv Detail & Related papers (2022-08-12T17:03:50Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.