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Abstract

The Smart City concept now entirely relies on information and communication technologies (ICT) with projects providing new or better services for city residents. The resilience of a city, from our perspective, should also rely on ICT. Resilience as a service implies predictive modelling and “what if” analysis for better reaction at unpredictable events and providing emergency services in critical modes of city life. Resilience as a property of a city means working as normally as possible for citizens when extreme events occur and also adaptively react and change the system’s behavior when normal mode has no chance to be applied. This paper provides a review and analysis of the resilient properties of existing Smart City frameworks and offers a new concept of a resilient city based on the Demand-Resource (DR) model, multi-agent system (MAS) and ontologies. The main idea of this concept is to create an ICT framework that is resilient by design. For this, it should operate as a digital ecosystem of smart services. The framework development process is divided into two main steps: first to create Smart City simulation software for modelling, planning, and strategic assessment of urban areas as a set of models at different levels of abstraction. The second step involves the full integration of all services in one dynamic adaptive real-time digital ecosystem with resilient properties.

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Acknowledgment

This work was supported by the AI & Reasoning project CZ.02.1.01/0.0/0.0/ 15_003/0000466, by the European Regional Development Fund and by the Technology Agency of the Czech Republic (TACR), National Competence Center of Cybernetics and Artificial Intelligence, TN01000024.

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Correspondence to Sergey Kozhevnikov .

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Kozhevnikov, S., Svitek, M., Skobelev, P. (2021). Multi-agent Approach for Smart Resilient City. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Lamouri, S. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2020. Studies in Computational Intelligence, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-69373-2_15

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