Digital twin as risk-free experimentation aid for techno-socio-economic systems
Conference paper
Barat, S., Kulkarni, V., Clark, T. and Barn, B. 2022. Digital twin as risk-free experimentation aid for techno-socio-economic systems. ACM / IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS). Montreal, Canada 23 - 28 Oct 2022 Association for Computing Machinery (ACM). pp. 66-75 https://doi.org/10.1145/3550355.3552409
Type | Conference paper |
---|---|
Title | Digital twin as risk-free experimentation aid for techno-socio-economic systems |
Authors | Barat, S., Kulkarni, V., Clark, T. and Barn, B. |
Abstract | Environmental uncertainties and hyperconnectivity force techno-socio-economic systems to introspect and adapt to succeed and survive. Current practice is chiefly intuition-driven which is inconsistent with the need for precision and rigor. We propose that this can be addressed through the use of digital twins by combining results from Modelling & Simulation, Artificial Intelligence, and Control Theory to create a risk free ‘in silico’ experimentation aid to help: (i) understand why system is the way it is, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. We use reinforcement learning to systematically explore the digital twin solution space. Our proposal is significant because it advances the effective use of digital twins to new problem domains that have greater impact potential. Our novel approach contributes a meta model for simulatable digital twin of industry scale techno-socio-economic systems, agent-based implementation of the digital twin, and an architecture that serves as a risk-free experimentation aid to support simulation-based evidence-backed decision-making. We also discuss validation of this approach, associated technology infrastructure, and architecture through a representative sample of industry-scale real-world use cases. |
Sustainable Development Goals | 9 Industry, innovation and infrastructure |
Research Group | Foundations of Computing group |
Conference | ACM / IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS) |
Page range | 66-75 |
ISBN | |
Hardcover | 9781450394666 |
Publisher | Association for Computing Machinery (ACM) |
Publication dates | |
24 Oct 2022 | |
Publication process dates | |
Deposited | 15 Jul 2022 |
Accepted | 13 Jul 2022 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | Copyright © ACM 2022. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in MODELS '22: Proceedings of the 25th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, http://dx.doi.org/10.1145/10.1145/3550355.3552409 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3550355.3552409 |
Language | English |
Book title | MODELS '22: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems |
https://repository.mdx.ac.uk/item/89xq1
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