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Thursday, March 12, 2015

Optimizations for Decision Making and Planning in Description Logic Dynamic Knowledge Bases. (arXiv:1502.04665v3 [cs.AI] UPDATED)

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. This developed in parallel with declarative approaches for modelling processes, where activities are not burdened by over-specified constrains like in traditional process-centric approaches, but try to adapt the internal system to the humans involved and the input they receive. In this paper, we try to merge these two aspects by proposing a framework 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. We then propose an evolution of such framework by introducing action rewriting and knowledge partialization: the resulting framework represents a viable and formal environment to develop decision making and planning techniques for DL-based artifact-centric business domains.






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