Abstract
Self-organized criticality (SOC) has been widely adopted as a useful paradigmatic generalization to capture an array of observations found to be intrinsic in many natural and human-made systems. It often manifests itself in the form of dynamic metastable patterns that are not attributable to any constituent element of the system. As our world becomes increasingly network centric, assessment of the emergent unpredictable fluctuations increasingly play an important role in understanding the system dynamics of society and economics. To date, complexity and SOC lack a systematic convergence of theoretical approaches and experimental methodologies. The attitude of many hard sciences in relation to complex systems can often be described as βthe elephant in the room,β a metaphorical idiom for an obvious truth that is largely ignored by scientists, even if recognized as critical in assessing risk and inherent uncertainty. Here we provide a brief background on the roles of SOC and emergence that seem to spontaneously appear with a plethora of spatial-temporal fluctuations on all scales. We propose that a deeper understanding of these phenomena requires a convergent effort of the sciences, arts, and humanities both in research and education. Further, it is proposed that a unified approach is necessary to achieve a more quantifiable, analytical, and predictive methodology to determining risk and resilience in complex systems with the goal of better understanding the world around us.
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References
Anderson PW (2011) More and different: notes from a thoughtful curmudgeon. World Scientific, Singapore, New Jersey
Ashby WR (1947) Principles of the self-organizing dynamic system. J Gen Psychol 37:125β128
Bak P (1999) How nature works: the science of self-organized criticality. Copernicus, New York
Bak P, Paczuski M (1995) Complexity, Contingency, and Criticality. Proceedings of the National Academy of Sciences 92:6689β6696
Barabasi A-L (2012) The network takeover. Nat Phys 8:15β16
Binder PM (2009) The edge of reductionism. Nature 459:332β333
Chialvo D (2014) In: A fundamental theory to model the mind, Jennifer Ouellette. Quanta Magazine, 3 Apr 2014. https://www.quantamagazine.org/20140403-a-fundamental-theory-to-model-the-mind/
De Wolf T, Holvoet T (2005) Emergence versus self-organisation: different concepts but promising when combined. In: Engineering self-organizing systems, Lecture notes in computer science. Springer, Berlin/Heidelberg
Gimzewski JK, Joachim C (1999) Nanoscale science of single molecules using local probes. Science 238(5408):1683β1688
Hazen R (2005) Genesis: the scientific quest for lifeβs origins. Joseph Henry Press, Washington, DC
Jensen HJ (1998) Self-Organized Criticality: Emergent Complex Behavior in Physical and Biological Systems. Cambridge University Press, Cambridge.
Johnson BR, Lam SK (2010) Self-organization, natural selection, and evolution: cellular hardware and genetic software. Bioscience 60(11):879β885
Kari L, Rozenberg G (2008) The many facets of natural computing. Commun ACM 51(10):72β83
Langton CG (1990) Computation at the edge of chaos: phase transitions and emergent computation. Physica D 42:12β37
LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521:436β444
Modha DS, Rajagopal A, Esser SK, Ndirango A, Sherbondy AK, Singh R (2011) Cognitive computing. Commun ACM 54(8):62β71
Nettesheim S, von Oertzen A, Rotermund HH, Ertl G (1993) Reaction diffusion patterns in the catalytic CO-oxidation on Pt(110)- front propagation and spiral waves. J Chem Phys 98:9977
Prigogine I (1997) The end of certainty. Free Press, New York
Proctor JD, Larson BMH (2005) Ecology, complexity, and metaphor. Bioscience 55(12):1065β1068
Stieg AZ, Avizienis AV, Sillin HO, Martin-Olmos C, Aono M, Gimzewski JK (2012) Emergent criticality of complex turing B-type atomic switch networks. Adv Mater 24:286β293
von Neumann J (1988) The principles of large scale computing machines. IEEE Ann Hist Comput 10:243
Weiner N (1961) Cybernetics or control and communication in the animal and the machine, 2nd edn. MIT Press, New York, Cambridge
Acknowledgments
JG thanks the Semiconductor Research Corporation (SRC); Japanese World Premiere Initiative program (WPI); International Center for Material Nanoarchitectonics (MANA) and DARPAβs Physical Intelligence program for inspiration and funding. VV acknowledges βMapping Acoustic Sensor Networksβ research, NSF grant no. IIS-1125423 (Charles Taylor, PI). We thank Renato Aguilera for useful discussions.
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Gimzewski, J.K., Stieg, A.Z., Vesna, V. (2015). Self-Organization and Emergence of Dynamic Systems. In: Bainbridge, W., Roco, M. (eds) Handbook of Science and Technology Convergence. Springer, Cham. https://doi.org/10.1007/978-3-319-04033-2_74-1
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DOI: https://doi.org/10.1007/978-3-319-04033-2_74-1
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