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Cities as Convergent Autopoietic Systems

In: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities

Author

Listed:
  • Christopher G. Kirwan

    (Henley Business School, University of Reading, Informatics Research Centre)

  • Stefan V. Dobrev

    (Maastricht University, School of Business and Economics)

Abstract

The aim of this paper is to explore the epistemological evolution of systems thinking, from cybernetics to autopoiesis and anticipatory systems in search of common characteristics, themes, and behaviors that define living, intelligent systems. Building on this theoretical foundation, we seek to establish the guiding principles behind a new bio-determinist paradigm for the future design and operations of complex urban systems (smart cities). We introduce the concept and vision of Autopoietic Operating Systems (AOS) to describe the total convergence of autopoietic properties required to manage diverse urban functions (Smart Environment, Smart Economy, Smart Mobility, Smart Governance, Smart People, and Smart Living) and the mechanisms that will enable cities to become intelligent, self-regulating ecosystems, coexisting in harmony with the natural environment.

Suggested Citation

  • Christopher G. Kirwan & Stefan V. Dobrev, 2022. "Cities as Convergent Autopoietic Systems," Springer Optimization and Its Applications, in: Panos M. Pardalos & Stamatina Th. Rassia & Arsenios Tsokas (ed.), Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities, pages 1-26, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-84459-2_1
    DOI: 10.1007/978-3-030-84459-2_1
    as

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