Resources

Foundational books by fellows:

  • Chilson, N. (2021). Getting Out Of Control: Emergent Leadership in a Complex World. New Degree Press.
  • Koppl, R. (2002). Big players and the economic theory of expectations. Springer.
  • Koppl, R. (2018). Expert failure. Cambridge University Press.
  • Koppl, R., Gatti, R.C., Devereaux, A., Herriot, J., Fath, B.D., Hordijk, W., Kauffman, S., Ulanowicz, R.E. and Valverde, S. (2023). Explaining technology. Elements in Evolutionary Economics, Cambridge University Press.
  • Potts, J. (2001). The New Evolutionary Microeconomics: Complexity, Competence and Adaptive Behaviour. Edward Elgar Publishing.
  • Potts, J. (2012). Creative Industries and Economic Evolution. Edward Elgar Publishing.
  • Potts, J. (2019). Innovation Commons: The Origin of Economic Growth. Oxford University Press.
  • Root, H. L. (2020). Network Origins of the Global Economy: East vs. West in a Complex Systems Perspective. Cambridge University Press.
  • Rosser, J. B. (2013). From catastrophe to chaos: a general theory of economic discontinuities. Springer Science & Business Media.
  • Rosser, J. B. (2021). Foundations and Applications of Complexity Economics (pp. 25-51). Springer.
  • Wagner, R. E. (2010). Mind, Society, and Human Action: Time and Knowledge in a Theory of Social-Economy. Routledge.
  • Wagner, R. E. (2016). Politics as a peculiar business: Insights from a theory of entangled political economy. Edward Elgar Publishing.
  • Wagner, R. E. (2020). Macroeconomics as Systems Theory: Transcending the Micro-Macro Dichotomy. Springer Nature.

Foundational books by non-fellows:

  • Bergson, H. (1911). Creative evolution. Henry Holt.
  • Cooper, S. B., & Soskova, M. I. (Eds.). (2017). The Incomputable. Springer International Publishing.
  • Day, R. H. (1994). Complex Economic Dynamics – Vol. 1: An Introduction to Dynamical Systems and Market Mechanisms. In MIT Press Books (Vol. 1). The MIT Press.
  • DeCanio, S. J. (2014). Limits of Economic and Social Knowledge. Palgrave Macmillan UK.
  • Epstein, J. M. (2006). Generative social science: Studies in agent-based computational modeling. Princeton University Press.
  • Kauffman, S. (1993). The origins of order: Self-organization and selection in evolution. Oxford University Press.
  • Latour, B. (2007). Reassembling the social: An introduction to actor-network-theory. Oxford.
  • Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge University Press.
  • Prigogine, I., & Stengers, I. (1997). The end of certainty. Simon and Schuster.
  • Shackle, G. L. S. (1972). Epistemics and economics.
  • Simon, H. A. (1996). The sciences of the artificial. MIT Press.
  • Smith, A. (2010). The theory of moral sentiments. Penguin.

Foundational edited volumes:

  • Chaitin, Doria, da Costa. Gödel’s Way: Exploits into an undecidable world.
  • Doria, F. A. (2017). The Limits of Mathematical Modeling in the Social Sciences: The Significance of Gödel’s Incompleteness Phenomenon. WORLD SCIENTIFIC (EUROPE). https://doi.org/10.1142/q0091
  • Zenil, H. (2012). A Computable Universe: Understanding and Exploring Nature as Computation. WORLD SCIENTIFIC. https://doi.org/10.1142/8306

Some foundational articles (including those by fellows):

  • Albin, P., & Foley, D. K. (1992). Decentralized, dispersed exchange without an auctioneer. Journal of Economic Behavior & Organization, 18(1), 27–51. https://doi.org/10.1016/0167-2681(92)90051-C
  • Axtell, R. (2003). Economics as Distributed Computation. In T. Terano, H. Deguchi, & K. Takadama (Eds.), Meeting the Challenge of Social Problems via Agent-Based Simulation (pp. 3–23). Springer Japan. https://doi.org/10.1007/978-4-431-67863-2_1
  • Axtell, R. (2005). The Complexity of Exchange. The Economic Journal, 115(504), F193–F210. https://doi.org/10.1111/j.1468-0297.2005.01001.x
  • Banks, J., & Potts, J. (2010). Co-creating games: A co-evolutionary analysis. New Media & Society, 12(2), 253–270. https://doi.org/10.1177/1461444809343563
  • Beckage, B., Kauffman, S., Gross, L. J., Zia, A., & Koliba, C. (2013). More Complex Complexity: Exploring the Nature of Computational Irreducibility across Physical, Biological, and Human Social Systems. In H. Zenil (Ed.), Irreducibility and Computational Equivalence (Vol. 2, pp. 79–88). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-35482-3_7
  • Banzhaf, W., Baumgaertner, B., Beslon, G., Doursat, R., Foster, J. A., McMullin, B., de Melo, V. V., Miconi, T., Spector, L., Stepney, S., & White, R. (2016). Defining and simulating open-ended novelty: Requirements, guidelines, and challenges. Theory in Biosciences, 135(3), 131–161. https://doi.org/10.1007/s12064-016-0229-7
  • Boulding, K. E. (1956). General Systems Theory: The Skeleton of Science. Management Science, 2(3), 13.
  • Burt, R. S. (2004). Structural Holes and Good Ideas. American Journal of Sociology, 110(2), 349–399. https://doi.org/10.1086/421787
  • Calude, C. S., & Longo, G. (2017). The Deluge of Spurious Correlations in Big Data. Foundations of Science, 22(3), 595–612. https://doi.org/10.1007/s10699-016-9489-4
  • Crutchfield, J. P. (2012). Between order and chaos. Nature Physics, 8(1), 17–24. https://doi.org/10.1038/nphys2190
  • Dopfer, K., Foster, J., & Potts, J. (2004). Micro-meso-macro. Journal of Evolutionary Economics, 14(3), 263–279. https://doi.org/10.1007/s00191-004-0193-0
  • Fiori, S. (2009). Hayek’s theory on complexity and knowledge: Dichotomies, levels of analysis, and bounded rationality. Journal of Economic Methodology, 16(3), 265–285. https://doi.org/10.1080/13501780903128548
  • Gaus, G.F. (2007), ‘Social Complexity and Evolved Moral Principles’, in Liberalism, Conservatism, and Hayek’s Idea of Spontaneous Order, eds. L. Hunt and P. McNamara, London: Palgrave Macmillan, pp. 149– 176.
  • Hayek, F. A. (1955). Degrees of Explanation. The British Journal for the Philosophy of Science, 6(23), 209–225.
  • Hayek, F. A. (1964). The theory of complex phenomena. In Critical Approaches to Science & Philosophy (pp. 332–349). Routledge.
  • Helbing, D., & Kirman, A. (2013). Rethinking economics using complexity theory. Real-World Economics Review, 64.
  • Hordijk, W. (2016). Evolution: Limited and Predictable or Unbounded and Lawless? Biological Theory, 11(4), 187–191. https://doi.org/10.1007/s13752-016-0251-5
  • Ioannidis, J. P. A. (2012). Why Science Is Not Necessarily Self-Correcting. Perspectives on Psychological Science, 7(6), 645–654. https://doi.org/10.1177/1745691612464056
  • Jackson, M. O., & Zenou, Y. (2015). Games on networks. In Handbook of game theory with economic applications (Vol. 4, pp. 95–163). Elsevier.
  • Kao, Y.-F., Ragupathy, V., Velupillai, K. V., & Zambelli, S. (2012). Noncomputability, unpredictability, undecidability, and unsolvability in economic and finance theories. Complexity, 18(1), 51–55. https://doi.org/10.1002/cplx.21410
  • Kauffman, S. A., & Roli, A. (2021). The Third Transition in Science: Beyond Newton and Quantum Mechanics — A Statistical Mechanics of Emergence. https://arxiv.org/abs/2106.15271v4
  • Kirman, A. P. (1992). Whom or What Does the Representative Individual Represent? Journal of Economic Perspectives, 6(2), 117–136. https://doi.org/10.1257/jep.6.2.117
  • Koppl, R., & Barkley Rosser Jr, J. (2002). All That I Have to Say Has Already Crossed Your Mind. Metroeconomica, 53(4), 339–360. https://doi.org/10.1111/1467-999X.00147
  • Koppl, R., Kauffman, S., Felin, T., & Longo, G. (2015). Economics for a creative world. Journal of Institutional Economics, 11(1), 1–31. https://doi.org/10.1017/S1744137414000150
  • Koppl, R. (2010). Some epistemological implications of economic complexity. Journal of Economic Behavior & Organization, 76(3), 859–872. https://doi.org/10.1016/j.jebo.2010.09.012
  • Lewis, A. A. (1985). On effectively computable realizations of choice functions. Mathematical Social Sciences, 10(1), 43–80. https://doi.org/10.1016/0165-4896(85)90038-1
  • Lewis, A. A. (1992). On turing degrees of Walrasian models and a general impossibility result in the theory of decision-making. Mathematical Social Sciences, 24(2–3), 141–171. https://doi.org/10.1016/0165-4896(92)90060-I
  • Lewis, P. (2015). Notions of order and process in Hayek: The significance of emergence. Cambridge Journal of Economics, 39(4), 1167–1190. https://doi.org/10.1093/cje/beu043
  • Long, N. E. (1958). The Local Community as an Ecology of Games. American Journal of Sociology, 64(3), 251–261.
  • McGinnis, M. D. (2011). Networks of Adjacent Action Situations in Polycentric Governance: McGinnis: Adjacent Action Situations. Policy Studies Journal, 39(1), 51–78. https://doi.org/10.1111/j.1541-0072.2010.00396.x
  • Rosser, J. Barkley. (1999). On the Complexities of Complex Economic Dynamics. The Journal of Economic Perspectives, 13(4), 169–192.
  • Rosser, J. B. (2014). Complexity and Behavioral Economics: (573792014-001) [Data set]. American Psychological Association. https://doi.org/10.1037/e573792014-001
  • Rosser, J. B. (2015). Complexity and Austrian Economics. In C. J. Coyne & P. Boettke (Eds.), The Oxford Handbook of Austrian Economics (pp. 593–611). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199811762.013.27
  • Smith, V. L. (2003). Constructivist and Ecological Rationality in Economics. American Economic Review, 93(3), 465–508. https://doi.org/10.1257/000282803322156954
  • Tesfatsion, L. (2002). Agent-based computational economics: Growing economies from the bottom up. Artificial life, 8(1), 55-82.
  • Tesfatsion, L. (2003). Agent-based computational economics: modeling economies as complex adaptive systems. Information sciences, 149(4), 262-268.
  • Tesfatsion, L. (2006). Agent-based computational economics: A constructive approach to economic theory. Handbook of computational economics, 2, 831-880.
  • Vaughn, K. I. (n.d.). Hayek’s Implicit Economics: Rules and the Problem of Order. 16.
  • Vaughn, K. I. (1999). Hayek’s theory of the market order as an instance of the theory of complex, adaptive systems. Journal Des Économistes et Des Études Humaines, 9(2–3). https://doi.org/10.1515/jeeh-1999-2-304
  • Wagner, R. E. (2012). A macro economy as an ecology of plans. Journal of Economic Behavior & Organization, 82(2–3), 433–444. https://doi.org/10.1016/j.jebo.2011.07.019
  • Wagner, R. E. (2016). Regarding the Use of Knowledge in Political Economy: Paretian Insight into a Hayekian Challenge. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2776985
  • Weaver, W. (1961). A Quarter Century in the Natural Sciences. Public Health Reports (1896-1970), 76(1), 57–65.
  • Weaver, W. (1948). Science and Complexity. In G. J. Klir, Facets of Systems Science (pp. 449–456). Springer US. https://doi.org/10.1007/978-1-4899-0718-9_30
  • Weimar, W.B. (1982), ‘Hayek’s Approach to the Problems of Complex Phenomena: An Introduction to the Theoretical Psychology of The Sensory Order’, in Cognition and the Symbolic Processes (Vol. 2), eds. W.B. Weimer and D.S. Palermo, Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 241– 285.
  • Wolpert, D. H. (2001). Computational capabilities of physical systems. Physical Review E, 65(1), 016128. https://doi.org/10.1103/PhysRevE.65.016128
  • Wolpert, D. H. (2008). Physical limits of inference. Physica D: Nonlinear Phenomena, 237(9), 1257–1281. https://doi.org/10.1016/j.physd.2008.03.040