Abstract
The purpose of this contribution is to outline the irreducible, analytically non-zippable, and theoretical incompleteness and quasi-ness of complexity. The neglect of such properties or their approximation by using non-complex systemic concepts and properties should be regarded as a new form of reductionism absolutely ineffective in dealing with complexity. We present characteristic issues of complexity such as Multiple Systems whose components interact in multiple ways and play multiple interchangeable roles; logical openness when complete modeling is not possible in face of the continuous restructuring of complex systems; theoretical incompleteness intended as inexhaustible, incomplete multiplicity necessary for processes of emergence; and quasi-ness related to levels of instabilities, irregular alternations of collapse and recovery, when a system is not always a system, not always the same system, and not only a system. We mention approaches such as the Dynamic Usage of Models (DYSAM) and the use of clustering, properties of clusters and infra-clusters, and properties of such properties. Given the non-idealistic (for instance mesoscopic) characteristics appropriate to the representations of complexity, the new reductionism consists in the neglect of logical openness, incompleteness, quasi-ness, and multiplicities, that is, of the conceptual space of freedom for processes of emergence to occur.
In memory of Eliano Pessa
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Notes
- 1.
The uncertainty associated with the location of a particle, denoted by Δx, and associated with its momentum, denoted by Δp, are connected by the Heisenberg relationship Δx Δp ≥ h/4π, where h is Planck’s constant.
References
Aggarwal, C. C., & Reddy, C. K. (2013). Data clustering: Algorithms and applications. CRC Press.
Ballarini, M., Cabibbo, N., Candelier, R., Cavagna, A., Cisbani, E., Giardina, I., Lecomte, V., Orlandi, A., Parisi, G., Procaccini, A., Viale, M., & Zdravkovic, V. (2008). Interaction ruling animal collective behaviour depends on topological rather than metric distance: Evidence from a field study. PNAS, 105(4), 1232–1237.
Blasone, M., Jizba, P., & Vitiello, G. (2011). Quantum field theory and its macroscopic manifestations. Imperial College Press.
Bonometti, P. (2012). Improving safety, quality and efficiency through the management of emerging processes: The Tenaris-Dalmine experience. The Learning Organization, 19, 299–310.
Boulis, C., & Ostendorf, M. (2004). Combining multiple clustering systems. In J. F. Boulicaut, F. Esposito, F. Giannotti, & D. Pedreschi (Eds.), Knowledge discovery in databases: PKDD 2004. PKDD 2004. Lecture Notes in Computer Science (Vol. 3202). Springer.
Brabazon, A., O’Neill, M., & McGarraghy, S. (2015). Natural computing algorithms. Springer.
Brovchenko, I., & Oleinikova, A. (2008). Multiple phases of liquid water. ChemPhysChem, 9(18), 2660–2675.
Brovchenko, I., Geiger, A., & Oleinikova, A. (2005). Liquid-liquid phase transitions in supercooled water studied by computer simulations of various water models. The Journal of Chemical Physics, 123(4), 44515.
Cavagna, A., Cimarelli, A., Giardina, I., Parisi, G., Santagati, R., Stefanini, F., & Viale, M. (2010). Scale-free correlations in starling flocks. Proceeding of the National Academy of Sciences of the United States of America, 107, 11865–11870. https://www.pnas.org/content/107/26/11865. Accessed September 17, 2019.
Diettrich, O. (2001). A physical approach to the construction of cognition and to cognitive evolution. Foundations of Science, 6, 273–341.
Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Cluster analysis. Wiley.
Feynmann, R. (1967). The character of physical law. The MIT Press.
Gambuzza, L. V., Cardillo, A., Fiasconaro, A., Fortuna, L., Gómez-Gardenes, J., & Frasca, M. (2013). Analysis of remote synchronization in complex networks. Chaos, 23, 1–8.
Licata, I., & Minati, G. (2016). Emergence, computation and the freedom degree loss information principle in complex systems. Foundations of Science, 21(3), 1–19.
Longo, G. (2011). Reflections on concrete incompleteness. Philosophia Mathematica, 19, 255–280.
Longo, G. (2019). Interfaces of incompleteness. In G. Minati, M. R. Abram, & E. Pessa (Eds.), Systemics of incompleteness and quasi-systems (pp. 3–55). Springer.
Mac Lennan, B. J. (2004). Natural computation and non-turing models of computation. Theoretical Computer Science, 317, 115–145.
Mikhailov, A. S., & Calenbuhr, V. (2002). From cells to societies. Models of complex coherent actions. Springer.
Minati, L. (2015). Remote synchronization of amplitudes across an experimental ring of non-linear oscillators. Chaos, 25, 123107–123112.
Minati, G. (2001). Experimenting with the dynamic usage of models (DYSAM) approach: The case of corporate communication and education. In CD-Proceedings of the 45th annual meeting of the international society for the systems sciences (ISSS). Monterey, California, July 8th–13th 2001; 01-094, pp. 1–15.
Minati, G. (2016a). Knowledge to manage the knowledge society: The concept of theoretical incompleteness. Systems, 4(3), 1–19. http://www.mdpi.com/2079-8954/4/3/26
Minati, G. (2016b). General system(s) theory 2.0: a brief outline, In G. Minati, M. Abram, & E. Pessa (Eds.), Towards a post-bertalanffy systemics (pp. 211–219). Springer.
Minati, G. (2018). The non-systemic usages of systems as reductionism. Quasi-systems and Quasi-systemics. Systems, 6(3). http://www.mdpi.com/2079-8954/6/3/28
Minati, G. (2019a). Phenomenological structural dynamics of emergence: An overview of how emergence emerges. In Urbani Ulivi Lucia (Ed.), The systemic turn in human and natural sciences. A rock in the pond. (pp. 1–39). Springer. https://www.springer.com/us/book/9783030007249
Minati, G. (2019b). A controversial issue: The intelligence of matter as residue? A possible understanding. Biomedical Journal of Scientific & Technical Research (BJSTR), 23(1), 17139–17140. https://biomedres.us/pdfs/BJSTR.MS.ID.003848.pdf
Minati, G. (2019c). Big data: From forecasting to mesoscopic understanding. Meta-profiling as complex systems. Systems, 7(1), 8. https://www.mdpi.com/2079-8954/7/1/8
Minati, G., (2019d), On some open issues in systemics. In G. Minati, A. Abram, & E. Pessa (Eds.), Systemics of incompleteness and quasi-systems (pp. 317–323). Springer.
Minati, G. (2019e). Non-classical systemics of quasi-coherence: From formal properties to representations of generative mechanisms. A conceptual introduction to a paradigm-shift. Systems, 7(4). https://www.mdpi.com/2079-8954/7/4/51
Minati, G., & Brahms, S. (2002). The dynamic usage of models (DYSAM). In G. Minati & E. Pessa (Eds.), Emergence in complex cognitive, social and biological systems (pp. 41–52). Kluwer.
Minati, G., & Licata, I. (2012). Meta-structural properties in collective behaviours. The International Journal of General Systems, 41(3), 289–311.
Minati, G., & Licata, I., (2013). Emergence as mesoscopic coherence. Systems, 1(4), 50–65. http://www.mdpi.com/2079-8954/1/4/50
Minati, G., & Licata, I., (2015). Meta-structures as multidynamics systems approach. Some introductory outlines. Journal on Systemics, Cybernetics and Informatics (JSCI), 13(4), 35–38. http://www.iiisci.org/journal/sci/issue.asp?is=ISS1504
Minati, G., & Pessa, E. (2006). Collective beings. Springer.
Minati, G., & Pessa, E. (2018). From collective beings to quasi-systems. Springer.
Minati, G., Penna, M. P., & Pessa, E. (1996). Towards a general theory of logically open systems. In E. Pessa, M. P. Penna, & A. Montesanto (Eds.), Proceedings of the 3rd systems science European congress, (Kappa, Rome, Italy, pp. 957–960).
Minati, G., Penna, M. P., & Pessa, E. (1998). Thermodynamic and logical openness in general systems. Systems Research and Behavioral Science, John Wiley and Sons Ltd., 15(3), 131–145.
Minati, G., Abram, M., & Pessa, E. (Eds.). (2016). Towards a post-Bertalanffy systemics. Springer.
Minati, G., Licata, I., & Pessa, E. (2013). Meta-structures: The search of coherence in collective behaviours (without physics). In Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, & Marco Antoniotti (Eds.), Proceedings Wivace 2013 – Italian Workshop on Artificial Life and Evolutionary Computation (Wivace 2013), Milan, Italy, July 1–2, 2013. Electronic Proceedings in Theoretical Computer Science (Vol. 130, pp. 35–42). http://rvg.web.cse.unsw.edu.au/eptcs/paper.cgi?Wivace2013.6
Minati, G., Abram, M., & Pessa, G. (Eds.) (2019). Systemics of incompleteness and quasi-systems. Springer. https://www.springer.com/gp/book/9783030152765
Miyamoto, S., Ichihashi, H., & Honda, K. (2008). Algorithms for fuzzy clustering: Methods in C-means clustering with applications. Springer.
Nicosia, V., Bianconi, G., Latora, V., & Barthelemy, M. (2013). Growing multiplex networks. Physical Review Letters, 111(058701), 1–5.
Ovelgӧnne, M., & Geyer-Schulz, A. (2013). An ensemble learning strategy for graph clustering. In D. A. Bader, H. Meyerhenke, P. Sanders, & D. Wagner (Eds.), Graph partitioning and graph clustering (Vol. 588, pp. 187–206). American Mathematical Society.
Paperin, G., Green, D. G., & Sadedin, S. (2011). Dual-phase evolution in complex adaptive systems. Interface, 8, 609–629.
Salgado, & Garrido, P.J. (2004). Fuzzy clustering of fuzzy systems. In IEEE International Conference on Systems, Man and Cybernetics (Vol. 3, pp. 2368–2373).
Solé, R. V. (2011). Phase transitions. Princeton University Press.
Transtrum, M. K., Machta, B. B., Brown, K.S., Daniels, B. C., Myers, C. R., & Sethna, J. P.: Perspective: Sloppiness and emergent theories in physics, biology, and beyond. Journal of Chemistry and Physics, 143, 010901.
Vicsek, T., & Zafeiris, A. (2012). Collective motion. Physics Reports, 517, 71–140.
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Minati, G. (2022). Multiplicity, Logical Openness, Incompleteness, and Quasi-ness as Peculiar Non-reductionist Properties of Complexity. In: Wuppuluri, S., Stewart, I. (eds) From Electrons to Elephants and Elections. The Frontiers Collection. Springer, Cham. https://doi.org/10.1007/978-3-030-92192-7_10
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