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Is There Anything New Under the Sun?

Instability as the Core of Emergence
  • Jan Cornelius SchmidtEmail author
Chapter

Abstract

This chapter aims to give substance to a contemporary understanding of emergence from the perspective of the philosophy of science. Looking at progress in the natural sciences, it draws on the concept of self-organization in order to provide a characterization of emergence. From the 1960s onward, theories of self-organization (including complex systems theory, nonlinear dynamics, chaos theory, synergetics, dissipative structures, fractal geometry, and autopoiesis theory) explicitly addressed emergent behavior. Referring to those theories, this chapter enquires into the ontological core as well as into the methodological and epistemological characteristics of self-organization—and, hence, of emergence. It is asked whether there is unity in the diversity of self-organizing phenomena in nature. It will be shown that instabilities constitute the ontological core of self-organization and are, therefore, central to any semantically meaningful understanding of emergence. Besides this ontological condition for the possibility of emergence (instability), the chapter also reveals that there are three further ontological characteristics of emergence, namely, (1) novelty, (2) processuality/temporality, (3) internality (“self”). In addition, related methodological and epistemological characteristics encompass: (4) limits in reproducibility/repeatability, (5) obstacles to predictability and (6) deficits in testability and reductive describability/explainability. In sum, since instabilities play a crucial role in nature, they are essential to any present-day concept of emergence.

Keywords

Progress in physical sciences Philosophy of science Emergence Self-organization Unity in diversity Instability New view of nature 

References

  1. Abarbanel HD, Brown R, Sidorowich JJ, Tsimring LS (1993) The analysis of observed chaotic data in physical systems. Rev Mod Phys 65:1331–1392CrossRefGoogle Scholar
  2. Andronov A, Pontryagin L (1937) Systèmes Grossiers. Dokl. Akad. Nauk. (Doklady) SSSR 14, pp 247–251Google Scholar
  3. Andronow A, Witt AA, Chaikin SE (1965/1969) Theorie der Schwingungen, Part I + II. Berlin, Akademie VerlagGoogle Scholar
  4. Atmanspacher H, Kurths J, Scheingraeber H, Wackerbauer R, Witt A (1992) Complexity and meaning in nonlinear dynamical systems. Open Syst Inform Dyn 1(2):269–289CrossRefGoogle Scholar
  5. Aubin D, Dalmedico AD (2002) Writing the history of dynamical systems and Chaos: Longue Durée and revolution. Discipl Cultures Hist Math 29:273–339CrossRefGoogle Scholar
  6. Aurell E, Boffetta G, Crisanti A, Paladin G, Vulpiani A (1997) Predictability in the large: an extension of the concept of Lyapunov exponent. J Phys A 30:1–26CrossRefGoogle Scholar
  7. Badii R (1991) Quantitative characterization of complexity and predictability. Phys Lett A 160:372–377CrossRefGoogle Scholar
  8. Banks J, Brooks J et al (1992) On Devaney’s definition of chaos. Am Math Monthly 99:332–334CrossRefGoogle Scholar
  9. Batterman R (2002) The devil in the detail: asymptotic reasoning in explanation, reduction and emergence. Oxford University Press, Oxford/New YorkGoogle Scholar
  10. Bergé P, Pomeau Y, Vidal C (1984) Order within chaos. Towards a deterministic approach to turbulence. Wiley, New YorkGoogle Scholar
  11. Birkhoff GD (1927) Dynamical systems. AMS Colloquium Publications, New YorkGoogle Scholar
  12. Böhme G, van den Daele W (1977) Erfahrung als Programm—Über Strukturen vorparadigmatischer Wissenschaft. In: Böhme G, van den Daele W, Krohn W (eds) Experimentelle Philosophie. Frankfurt, Suhrkamp, pp 166–219Google Scholar
  13. Brown R, Chua LO (1996) Clarifying chaos: examples and counterexamples. Int J Bif Chaos 6(2):219–249CrossRefGoogle Scholar
  14. Brown R, Chua LO (1998) Clarifying Chaos II: Bernoulli chaos, zero Lyapunov exponents and strange attractors. Int J Bif Chaos 8(1):1–32CrossRefGoogle Scholar
  15. Bunge M (1987) Kausalität. Geschichte und Probleme. Mohr, TübingenGoogle Scholar
  16. Carnap R (1928) Der logische Aufbau der Welt. Weltkreisverlag, BerlinGoogle Scholar
  17. Cartwright N (1983) How the laws of physics lie. Oxford University Press, OxfordCrossRefGoogle Scholar
  18. Cartwright N (1994) Nature’s capacities and their measurement. Oxford University Press, OxfordCrossRefGoogle Scholar
  19. Chaitin GJ (1971) Computational complexity and Gödel’s incompleteness theorem. ACM SIGACT News 9:11–12CrossRefGoogle Scholar
  20. Chaitin GJ (1987) Algorithmic information theory. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  21. Chaitin GJ (2001) Exploring randomness. Springer, LondonCrossRefGoogle Scholar
  22. Comte A (2006) Cours de Philosophie positive (1830–1842). Bachelier, ParisGoogle Scholar
  23. Coven E, Kan I, Yorke JA (1988) Pseudo-orbit shadowing in the family of tent maps. Trans Am Math Soc 308(1):227–241CrossRefGoogle Scholar
  24. Crutchfield J, Farmer JD, Packard NH, Shaw RS (1986) Chaos. Sci Am 12:46–57CrossRefGoogle Scholar
  25. Darrigol O (2006) Worlds of flow. A history of hydrodynamics from Bernoulli to Prandtl. Oxford University Press, OxfordGoogle Scholar
  26. Descartes R (1979) Regeln zur Ausrichtung der Erkenntniskraft. Felix Meixner, HamburgGoogle Scholar
  27. Devaney RL (1987) An introduction to chaotic dynamical systems. Addison Wesley, Redwood CityGoogle Scholar
  28. Drieschner (2002) Moderne Naturphilosophie. Eine Einführung. Paderborn, MentisGoogle Scholar
  29. Duhem P (1991) The aim and structure of physical theory (1906). Princeton Uni Press, PrincetonGoogle Scholar
  30. Ebeling W, Feistel R (1990) Physik der Evolutionsprozesse. Akademie Verlag, BerlinGoogle Scholar
  31. Einstein A (1917) Kosmologische Betrachtungen zur allgemeinen Relativitätstheorie. Sitzungsberichte der Königlich Preussischen Akademie der Wissenschaften, physikalisch-mathematische Klasse, pp 142–152Google Scholar
  32. Einstein A, Podolsky B, Rosen N (1935) Can quantum-mechanical description of physical reality be considered complete? Phys Rev 47:777–780CrossRefGoogle Scholar
  33. Gierer A (1981) Physik der biologischen Gestaltbildung. Naturwiss 68:245–251CrossRefGoogle Scholar
  34. Gleick J (1987) Chaos: making a new science. Viking Penguin, New YorkGoogle Scholar
  35. Guckenheimer J, Holmes P (1983) Nonlinear oscillations, dynamical systems, and bifurcations of vector fields. Springer, New YorkCrossRefGoogle Scholar
  36. Habermas J (1972) Knowledge and human interest (1968). Heinemann, LondonGoogle Scholar
  37. Hacking I (1983) Representing and intervening. Introductory topics in the philosophy of natural sciences. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  38. Haken H (ed) (1977) Synergetics. A workshop. Springer, BerlinGoogle Scholar
  39. Harrell M, Glymour C (2002) Confirmation and chaos. Philos Sci 69:256–265CrossRefGoogle Scholar
  40. Hartmann S, Frigg R (2006) Models in science. In: Zalta EN (ed) Stanford encyclopedia of philosophy. Stanford University Press, StanfordGoogle Scholar
  41. Heidegger M (1986) Nietzsches metaphysische Grundstellung im abendländischen Denken—die ewige Wiederkehr des Gleichen. Vittorio Klostermann, FrankfurtGoogle Scholar
  42. Hempel CG (1965) Aspects of scientific explanation. Free Press, New YorkGoogle Scholar
  43. Hertz H (1963) Die Prinzipien der Mechanik. In neuem Zusammenhang dargestellt (1894). Wiss. Buchgesellschaft, DarmstadtGoogle Scholar
  44. Hirsch M (1984) The dynamical systems approach to differential equations. Bull Am Math Soc 11:1–64CrossRefGoogle Scholar
  45. Holmes P (2005) Ninety plus thirty years of nonlinear dynamics: more is different and less is more. Int J Bif Chaos 15(9):2703–2716CrossRefGoogle Scholar
  46. Hooker CA (2004) Asymptotics, reduction and emergence. Brit J Phil Sci 55(3):435–479CrossRefGoogle Scholar
  47. Hume D (1990) Enquiries concerning human understanding (1748). Clarendon Press, OxfordGoogle Scholar
  48. Hund F (1972) Geschichte der physikalischen Begriffe. BI, MannheimGoogle Scholar
  49. Jackson EA (1989) Perspectives of nonlinear dynamics. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  50. Janich P (1997) Kleine Philosophie der Naturwissenschaften. Beck, MünchenGoogle Scholar
  51. Kellert S (1993) In the wake of chaos: unpredictable order in dynamical systems. University Chicago Press, ChicagoCrossRefGoogle Scholar
  52. Krohn W, Küppers G (eds) (1992) Selbstorganisation. Aspekte einer wissenschaftlichen Revolution. Vieweg, Braunschweig/WiesbadenGoogle Scholar
  53. Küppers B-O (1992) Naturals Organismus. Schellings frühe Naturphilosophie und ihre Bedeutung für die moderne Biologie. Suhrkamp, FrankfurtGoogle Scholar
  54. Langer JS (1980) Instabilities and pattern formation. Rev Mod Phys 52:1–28CrossRefGoogle Scholar
  55. Lenhard J (2007) Computer simulations: The cooperation between experimenting and modeling. Philos Sci 74:176–194CrossRefGoogle Scholar
  56. Lewes GH (1875) Problems of life and mind, first series, vol 2. Trubner, Kegan and others, LondonGoogle Scholar
  57. Li T-Y, Yorke JA (1975) Period three implies chaos. Am Math Monthly 82(10):985–992CrossRefGoogle Scholar
  58. Lorenz EN (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141CrossRefGoogle Scholar
  59. Lorenz EN (1989) Computational chaos—a prelude to computational instability. Phys D 35:299–317CrossRefGoogle Scholar
  60. Mach E (1988) Die Mechanik in ihrer Entwicklung (1883). Akademie Verlag, Leipzig/DarmstadtGoogle Scholar
  61. Mainzer K (1996) Thinking in complexity. The complex dynamics of matter, mind, and mankind. Heidelberg/New York: SpringerGoogle Scholar
  62. Mandelbrot B (1991) Die fraktale Geometrie der Natur (1977). Basel: BirkhauserGoogle Scholar
  63. Maxwell JC (1873) Does the progress of physical science tend to give any advantage to the opinion of necessity (or determinism) over that of the contingency of events and the freedom of the will? In: Campbell L, Garnett W (eds) The life of James Clerk Maxwell. Johnson, New York, pp 434–444Google Scholar
  64. Maxwell JC (1991) Matter and motion (1877). Dover Publications, New YorkGoogle Scholar
  65. Meinhardt H (1995) The algorithmic beauty of seashells. Springer, BerlinCrossRefGoogle Scholar
  66. Mitchell SD (2002) Integrative Pluralism. Biol Philos 17:55–70CrossRefGoogle Scholar
  67. Mittelstraß J (1998) Die Haeuser des Wissens. Suhrkamp, FrankfurtGoogle Scholar
  68. Morgan MS, Morrison M (eds) (1999) Models as mediators. Perspectives on natural and social sciences. Cambridge University Press, CambridgeGoogle Scholar
  69. Newton I (1770) Opticks: or, a treatise of the reflections, refractions, inflections and colours of light. Innys, New York, 1730 (1717)Google Scholar
  70. Nicolis G, Prigogine I (1977) Self-organization in nonequilibrium systems. From dissipative structures to order through fluctuations. Wiley, New York/LondonGoogle Scholar
  71. Nietzsche F (1930) Die fröhliche Wissenschaft (1887). Leipzig: KroenerGoogle Scholar
  72. Parker TS, Chua LO (1989) Practical numerical algorithms for chaotic systems. Springer, New YorkCrossRefGoogle Scholar
  73. Pauli W (1961) Aufsaetze und Vortraege über Physik und Erkenntnistheorie. Vieweg, BraunschweigCrossRefGoogle Scholar
  74. Peitgen H-O, Jürgens H, Saupe D (1992) Bausteine des Chaos: Fraktale. Springer/Klett-Cotta, BerlinCrossRefGoogle Scholar
  75. Pietschmann H (1996) Phaenomenologie der Naturwissenschaft. Springer, BerlinCrossRefGoogle Scholar
  76. Poincaré H (1892) Les méthodes nouvelles de la mécanique céleste. Gauthier-Villars et fils, Paris, p 1892Google Scholar
  77. Poincaré H (1914) Wissenschaft und Methode (1908). Teubner, LeipzigGoogle Scholar
  78. Popper KR (1934) Logik der Forschung. Wien: Julius Springer (English translation: the logic of scientific discovery. Routledge, London)Google Scholar
  79. Poser H (2001) Wissenschaftstheorie. Reclam, StuttgartGoogle Scholar
  80. Prigogine I, Glansdorff P (1971) Thermodynamic theory of structure, stability and fluctuation. Wiley, New York/LondonGoogle Scholar
  81. Prigogine I (1980) From being to becoming. Time and complexity in the physical sciences. Freeman, New YorkGoogle Scholar
  82. Psillos S (1999) Scientific realism. How science tracks truth. Routledge, London/New YorkGoogle Scholar
  83. Redhead M (1980) Models in physics. Brit J Phil Sci 31:145–163CrossRefGoogle Scholar
  84. Rueger A, Sharp AD (1996) Simple theories of a messy world: truth and explanatory power in nonlinear dynamics. Brit J Phil Sci 47:93–112CrossRefGoogle Scholar
  85. Ruelle D (1989) Elements of differentiable dynamics and bifurcation theory. Academic Press, London, p 1989Google Scholar
  86. Ruelle D, Takens F (1971) On the nature of turbulence. Commun Math Phys 20:167–192CrossRefGoogle Scholar
  87. Salmon W (1989) Four decades of scientific explanation. In: Kitcher P, Salmon W (eds) Scientific explanation. Minnesota: University Minnesota Press, pp 3–219Google Scholar
  88. Sauer T, Yorke JA, Casdagli M (1991) Embedology. J Stat Phys 77(3/4):579–616CrossRefGoogle Scholar
  89. Schmidt JC (2003) Zwischen Berechenbarkeit und Nichtberechenbarkeit. Die Thematisierung der Berechenbarkeit in der aktuellen Physik komplexer Systeme. J Gen Phil Sci 34:99–131Google Scholar
  90. Schmidt JC (2008a) From symmetry to complexity: on instabilities and the unity in diversity in nonlinear science. Int J Bif Chaos 18(4):897–910CrossRefGoogle Scholar
  91. Schmidt JC (2008b) Instabilität in Natur und Wissenschaft. Eine Wissenschaftsphilosophie der nachmodernen Physik. De Gruyter, BerlinCrossRefGoogle Scholar
  92. Schmidt JC (2015) Das Andere der Natur. Neue Wege zur Naturphilosophie, StuttgartGoogle Scholar
  93. Schmidt JC (2017) Science in an unstable world. On Pierre Duhem’s challenge to the methodology of science. In: Pietsch W, Wernecke J, Ott M (Hg.) (eds) (2017) Berechenbarkeit der Welt? Philosophie und Wissenschaft im Zeitalter von big data. Springer, Berlin, pp 403–434Google Scholar
  94. Stephan A (2007) Emergenz. Von der Unvorhersagbarkeit zur Selbstorganisation (1999). Mentis, PaderbornGoogle Scholar
  95. Swinney HL, Gollub J (eds) (1981) Hydrodynamic instabilities and the transition to turbulence. Springer, BerlinGoogle Scholar
  96. Takens F (1985) Distinguishing deterministic and random systems. In: Barenblatt GI, Ioss G, Joseph D (eds) (1985) Nonlinear dynamics and turbulence. Pitman, Boston, pp 314–333Google Scholar
  97. Thom R (1975) Structural stability and morphogenesis. An outline of a general theory of models. Benjamin, Reading/MAGoogle Scholar
  98. Vuillemin J (1991) Introduction. In: Duhem P (ed) (1991) The aim and structure of physical theory (1906). Princeton University Press, Princeton, pp xv–xxxiiiGoogle Scholar
  99. Wackerbauer R, Witt A, Atmanspacher H, Kurths J, Scheingraber H (1994) A comparative classification of complexity measures. Chaos, Solit Fract 4(1):133–174CrossRefGoogle Scholar
  100. Weizsäcker CFv (1974) Die Einheit der Natur. München: dtvGoogle Scholar
  101. Wiggins S (1988) Global bifurcations and chaos. Analytical methods. Springer, New YorkCrossRefGoogle Scholar
  102. Woodward J (2000) Explanation and invariance in the special sciences. Brit J Phil Sci 51:197–254CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Philosophy of Science and Technology, Department of Social SciencesDarmstadt University of Applied SciencesDarmstadtGermany

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