XPlaM: A toolkit for automating the acquisition of BDI agent-based Digital Twins of organizations

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Computers in Industry


A Digital Twin ideally manifests the same behaviour (in silico) of its physical counterpart. While considerable attention has been paid to the development of Digital Twins for physical devices/systems, the question of developing Twins for organizations has received relatively little attention. The setting in which we address this problem is very general and, consequently, very challenging. We look at the automatic acquisition of Digital Twins of organizations. To that end, this paper builds on the following two premises: (1) that Digital Twins of organizations can provide value, and (2) that Belief-Desire-Intention (BDI) agents are a particularly effective means for representing Digital Twins. The overall approach is to leverage the externally observable behaviour of the target system and then generate candidate BDI agent programs that best explain (in the sense of formal abduction) the observed behaviour. The candidate agent programs are generated by searching through potentially large hypotheses spaces for possible plans, selection functions and beliefs. The resulting approach suggests that using abduction to generate Digital Twins of organizations in the form of BDI agents can be effective.

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