Abstract
Historically, in science and philosophy people believed in a sharp difference between “dead” and “living” matter. Aristotle interpreted life as the power of self-organization (entelechy) driving the growth of plants and animals to their final form. A living system is able to reproduce itself and to move by itself, while a dead system can only be copied and moved from outside. Life was explained by teleology, i.e., by non-causal (“vital”) forces aiming at some goals in nature. In the eighteenth century Kant showed that self-organization of living organisms cannot be explained by a mechanical system of Newtonian physics. In a famous quotation he said that the Newton for explaining a blade of grass was still lacking. Nowadays, children put the same question: How is it possible that complex organisms such as plants, animals, and even humans emerge from the interactions of simple elements such as atoms, molecules, or cells? The concept of cellular automata was the first mathematical model to prove that self-reproduction and self-organization of complex patterns from simple rules are universal features of dynamical systems. Therefore, the belief in some preprogrammed intelligent design is unnecessary.
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References
U. Alon, Biological networks: the tinkerer as an engineer. Science 301, 1866–1867 (2003)
U. Alon, An Introduction to Systems Biology Design Principles of Biological Circuits (Chapman & Hall/CRC, London, 2006)
L.O. Chua, Memristor–the missing circuit element. IEEE Trans. Circuit Theory 18, 507–519 (1971)
L.O. Chua, CNN: A Paradigm for Complexity (World Scientific, Singapore, 1998)
L.O. Chua, Resistance switching memories are memristors. Appl. Phys. A 102(4), 765–783 (2011)
L.O. Chua, T. Roska, Cellular Neural Networks and Visual Computing: Foundations and Applications (Cambridge University Press, Cambridge, 2002)
M. Creutz, Cellular automata and self-organized criticality. in Some New Directions in Science on Computers, ed. by G. Bhanot, S. Chen, P. Seiden. (Singapore, World Scientific, 1997), pp. 147–169
M. Gardner, The fantastic combinations of John Conway’s new solitaire game of life. Sci. Am. 223, 120–123 (1970)
M. Gardner, Mathematical games: on cellular automata, self-reproduction, the Garden of Eden, and the game “Life”. Sci. Am. 224(2), 112–117 (1971)
G. Gerisch, B. Hess, Cyclic-AMP-controlled oscillations in suspended dictyostelium cells: their relation to morphogenetic cell interactions. Proc. Natl. Acad. Sci. 71, 2118 (1974)
H. Haken, A. Mikhailov (eds.), Interdisciplinary Approaches to Nonlinear Complex Systems (Springer, New York, 1993)
B. Hayes, The memristor. Am. Sci. 9(2), 106–110 (2011)
Y. Kayama, Complex networks derived from cellular automata (Cornell University arxiv.1009.4509v1, 2010)
A. Kriete, R. Eils (eds.), Computational System Biology (Elsevier, Amsterdam, 2006)
K. Mainzer, Cellular Neural Networks and visual computing. Int. J. Bifurc. Chaos 13(1), 1–6 (2003)
K. Mainzer, Thinking in Complexity. The Computational Dynamics of Matter, Mind, and Mankind, 5th edn. (Springer, Berlin, 2007)
K. Mainzer, Leben als Maschine? Von der Systembiologie zur Robotik und Künstlichen Intelligenz (Paderborn, Mentis, 2010)
J. Mullins, Memristor minds: the future of artificial intelligence. New Scientist 7 (2009)
D.B. Strukov, G.S. Snider, R. Duncan, D.R. Stewart, R.S. Williams, The missing memristor found. Nature 453, 80–83 (2008)
R. Tetzlaff (ed.), Cellular Neural Networks and their Applications (World Scientific, Singapore, 2002)
P. Topa, Network systems modelled by complex cellular automata paradigm. in Cellular Automata-Simplicity behind Complexity, ed. by A. Salcido. (InTech, 2011), pp. 259–274
A.M. Turing, The chemical basis of morphogenesis. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 237(641), 37–72 (1952)
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© 2012 Klaus Mainzer
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Mainzer, K., Chua, L. (2012). Life and Brain in the Universe of Cellular Automata. In: The Universe as Automaton. SpringerBriefs in Complexity. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23477-4_8
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DOI: https://doi.org/10.1007/978-3-642-23477-4_8
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