Optimizations for Decision Making and Planning in Description Logic Dynamic Knowledge Bases

TL;DR

This paper introduces a framework called Dynamic Knowledge Bases that combines Description Logic ontologies with actions for evolving business process models, enabling decision making and planning in artifact-centric domains.

Contribution

It proposes a formal environment integrating DL-based ontologies with action rewriting and knowledge partialization for planning in business process models.

Findings

Framework supports rich business domain modeling.

Enables decision making and planning in DL-based systems.

Formalizes evolution of knowledge bases through actions.

Abstract

Artifact-centric models for business processes recently raised a lot of attention, as they manage to combine structural (i.e. data related) with dynamical (i.e. process related) aspects in a seamless way. Many frameworks developed under this approach, although, are not built explicitly for planning, one of the most prominent operations related to business processes. In this paper, we try to overcome this by proposing a framework named Dynamic Knowledge Bases, aimed at describing rich business domains through Description Logic-based ontologies, and where a set of actions allows the system to evolve by modifying such ontologies. This framework, by offering action rewriting and knowledge partialization, represents a viable and formal environment to develop decision making and planning techniques for DL-based artifact-centric business domains.