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The project as a system. Inducing emergence of a system rather than designing a system
Author(s) -
Gianfranco Minati
Publication year - 2020
Publication title -
acta europeana systemica
Language(s) - English
Resource type - Journals
eISSN - 2225-9635
pISSN - 2225-9627
DOI - 10.14428/aes.v4i1.57053
Subject(s) - coherence (philosophical gambling strategy) , computer science , completeness (order theory) , field (mathematics) , complex system , management science , theoretical computer science , artificial intelligence , mathematics , mathematical analysis , pure mathematics , statistics , economics
In this article we consider how the activity of design and manage a system within the conceptual framework of the classical systemics assumes validity of concepts and approaches based, for instance, on explicit and symbolic representations; completeness; explicit decisions; adoption of control, degrees of freedom, optimisation, regulation and planning. Complex systems instead require different approaches since they are combinations of functioning and emergence. The systemics of complexity is rather based on concepts like coherence; incompleteness; induction; multiplicity of representations, levels of descriptions, and models; multiple systems; nonexplicitness; non-invasiveness; non-prescribability; structural dynamics; and usage of degrees of freedom. This requires new competences and approach for the managerial activity in any field by using new appropriated knowledge and approaches in order to combine, i.e., allow multiple usages of design and emergence, to induce, keep and act on complex systems. Keywordscombination, complexity, emergence, multiplicity, systemic. I . INTRODUCTION: COMPLETE-INCOMPLETE Classic systemics introduced by Bertalanffy and successively elaborated in a huge variety of contributions is based on some epistemological assumptions like 1. Completeness; 2. Possibility to control; 3. Possibility to take the best decision; 4. Degrees of freedom; 5. Possibility to forecast; 6. Possibility to set objectives; 7. Optimisation always possible; 8. Possibility to plan; 9. Reversibility; 10. Separability and unconnectedness. 11. solvability 12. symbolic modelling; and 13. Standardisation. Complexity deals with negations of such assumptions. For instance with theoretical incompleteness as introduced by Logical Openness [1, 2]. Logical openness considers phenomena, such as system-environment and phenomenon-observer interactions, that can not be described: explicitly, i.e., by using analytical models like equations; completely, and Acta Europeana Systemica n°4

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