Abstract
Natural complex adaptive systems are of particular scientific interest in many domains, as they may produce something new, like structures, patterns, or properties, that arise from the rules of self-organization. These novelties are emergent if they cannot be understood as any property of the components, but as a new property of the system. One of the leading methods to better understand complex adaptive systems is the use of their computational representation. In this paper, we make the case that emergence in computational complex adaptive systems can only be epistemological, as the constraints of computer functions do not allow for the creation of something new, as required for ontological emergence. As such, computer representations of complex adaptive systems are limited in producing emergence, but nonetheless useful to better understand the relationship between emergence and complex adaptive systems.
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References
Axtell, R.: Why Agents? on the Varied Motivations for Agent Computing in the Social Sciences. Center on Social and Economic Dynamics Brookings Institution, Washington, DC (2000)
Bankes, S.C.: Agent-based modeling: a revolution? Proc. Natl. Acad. Sci. 99(suppl 3), 7199–7200 (2002)
Beckner, C., Blythe, R., Bybee, J., Christiansen, M.H., Croft, W., Ellis, N.C., Holland, J., Ke, J., Larsen-Freeman, D., Schoenemann, T.: Language is a complex adaptive system: position paper. Lang. Learn. 59(s1), 1–26 (2009)
Boden, M.A.: Computer models of creativity. AI Mag. 30(3), 23 (2009)
Brownlee, J.: Complex adaptive systems. Complex Intelligent Systems Laboratory, Centre for Information Technology Research, Faculty of Information Communication Technology, Swinburne University of Technology, Melbourne, Australia (2007)
Buckley, W.: Society as a complex adaptive system. In: Modern Systems Research for the Behavioral Scientist. Aldine Publishing Company (1968)
Buss, S., Papadimitriou, C.H., Tsitsiklis, N.: On the predictability of coupled automata: an allegory about chaos. In: 1990 Proceedings of the 31st Annual Symposium on Foundations of Computer Science, pp. 788–793. IEEE (1990)
Choi, T.Y., Dooley, K.J., Rungtusanatham, M.: Supply networks and complex adaptive systems: control versus emergence. J. Oper. Manage. 19(3), 351–366 (2001)
Dooley, K.: Complex adaptive systems: a nominal definition. Chaos Netw. 8(1), 2–3 (1996)
Dreyfus, H.L.: What Computers Can’t Do: The Limits of Artificial Intelligence. Harper & Row, New York (1972)
Dreyfus, H.L.: What Computers Still Can’t Do: A Critique of Artificial Reason. MIT Press, Boston (1992)
Godschalk, D.R.: Urban hazard mitigation: creating resilient cities. Nat. Hazards Rev. 4(3), 136–143 (2003)
Hébert-Dufresne, L., Pellegrini, A.F., Bhat, U., Redner, S., Pacala, S.W., Berdahl, A.M.: Edge fires drive the shape and stability of tropical forests. Ecol. Lett. 21(6), 794–803 (2018)
Holland, J.H.: Complex adaptive systems. Daedalus 17–30 (1992)
Holland, J.H.: Hidden Order: How Adaptation Builds Complexity. Addison Wesley Publishing Company, Boston (1995)
Humphreys, P.: Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford University Press, Oxford (2004)
Ingwersen, W.W., Garmestani, A.S., Gonzalez, M.A., Templeton, J.J.: A systems perspective on responses to climate change. Clean Technol. Environ. Policy 16(4), 719–730 (2014)
Kauffman, S.A.: The origins of order: self-organization and selection in evolution. In: Spin Glasses and Biology, pp. 61–100. World Scientific (1992)
Levin, S.A.: Ecosystems and the biosphere as complex adaptive systems. Ecosystems 1(5), 431–436 (1998)
Lewes, G.H.: Problems of Life and Mind. Trübner & Company, London (1877)
Maier, M.W.: The role of modeling and simulation in system of systems development. In: Rainey, L.B., Tolk, A. (eds.) Modeling and Simulation Support for System of Systems Engineering Applications. Wiley (2015)
McCarthy, I.P., Tsinopoulos, C., Allen, P., Rose-Anderssen, C.: New product development as a complex adaptive system of decisions. J. Prod. Innov. Manage. 23(5), 437–456 (2006)
Miller, J.H., Page, S.E.: Complex Adaptive Systems: An Introduction to Computational Models of Social Life: An Introduction To Computational Models of Social Life. Princeton University Press, Princeton (2009)
Norman, M.D., Koehler, M.T., Pitsko, R.: Applied complexity science: enabling emergence through heuristics and simulations. In: Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach, pp. 201–226 (2018)
O’Connor, T., Wong, H.Y.: Emergent properties. In: Zalta, E.N. (ed.) The Stanford Encyclopedia of Philosophy, Summer 2015 edn. Metaphysics Research Lab, Stanford University (2015)
Payne, J.L., Khalid, F., Wagner, A.: RNA-mediated gene regulation is less evolvable than transcriptional regulation. Proc. Natl. Acad. Sci. 201719138 (2018)
Rouse, W.B.: Engineering complex systems: implications for research in systems engineering. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 33(2), 154–156 (2003)
Rouse, W.B.: Health care as a complex adaptive system: implications for design and management. Bridge Wash. Natl. Acad. Eng. 38(1), 17 (2008)
Sheard, S.A., Mostashari, A.: Principles of complex systems for systems engineering. Syst. Eng. 12(4), 295–311 (2009)
Silberstein, M., McGeever, J.: The search for ontological emergence. Philos. Q. 49(195), 201–214 (1999)
Tolk, A.: Simulation and modeling as the essence of computational science. In: Proceedings of the 50th Summer Computer Simulation Conference (2018)
Tolk, A., Diallo, S., Mittal, S.: Complex systems engineering and the challenge of emergence. In: Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach, pp. 79–97. Wiley (2018)
Zeigler, B.P., Mittal, S.: System theoretic foundations for emerging behavior modeling: the case of emergence of human language in a resource-constrained complex intelligent dynamical system. In: Emergent Behavior in Complex Systems Engineering: A Modeling and Simulation Approach, pp. 35–57. Wiley (2018)
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Tolk, A., Koehler, M.T.K., Norman, M.D. (2018). Epistemological Constraints When Evaluating Ontological Emergence with Computational Complex Adaptive Systems. In: Morales, A., Gershenson, C., Braha, D., Minai, A., Bar-Yam, Y. (eds) Unifying Themes in Complex Systems IX. ICCS 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-96661-8_1
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