Decidable Verification of Agent-Based Data-Aware Systems

2019 
In recent years the area of knowledge representation and reasoning (KR&R) has witnessed a growing interest in the modelling and analysis of data-driven/data-centric systems. These are systems in which the two tenets of data and processes are given equal importance, differently from traditional approaches whereby the data content is typically abstracted away in order to make the reasoning task easier. However, if data-aware systems (DaS) are to be deployed in concrete KR&R scenarios, it is key to develop tailored verification techniques, suitable to account for both data and processes. In this contribution we consider for the first time to our knowledge the parameterised verification of DaS. In particular, we prove that – under specific assumptions – this problem is decidable by computing a suitable cut-off value. We illustrate the proposed approach with a use case from the literature on business process modelling.
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