Abstract
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. This paper seeks to address this gap. The starting point is a log of an organization’s externally manifested behaviour that we seek to recreate via a Digital Twin represented as a BDI agent. We present an algorithm to explain the externally visible behaviour of the organization by positing a BDI agent plan library, which, if executed, would manifest the same behaviour. We also present an algorithm to infer the internal behaviour of the agent in terms of event, option, and intention selection functions. 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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Alelaimat, A., Ghose, A., Dam, H.K. (2021). Abductive Design of BDI Agent-Based Digital Twins of Organizations. In: Uchiya, T., Bai, Q., Marsá Maestre, I. (eds) PRIMA 2020: Principles and Practice of Multi-Agent Systems. PRIMA 2020. Lecture Notes in Computer Science(), vol 12568. Springer, Cham. https://doi.org/10.1007/978-3-030-69322-0_27
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