Abstract
Simulations are usually directed at some version of the question: What is the relationship between the individual actor and the collective community? Among social scientists, this question generally falls under the topic of emergence. Sociological theorists and philosophers of science have developed sophisticated approaches to emergence, including the critical question: to what extent can emergent phenomena be reduced to explanations in terms of their components? Modelers often proceed without considering these issues; the risk is that one might develop a simulation that does not accurately reflect the observed empirical facts or one that implicitly sides with one side of a theoretical debate that remains unresolved. In this chapter, I provide some tips for those developing simulations, by drawing on a strong recent tradition of analyzing scientific explanation that is found primarily in the philosophy of science but also to some extent in sociology.
Similar content being viewed by others
References
Axelrod, R. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton, NJ: Princeton University Press.
Bechtel, W. (2001). The compatibility of complex systems and reduction: A case analysis of memory research. Minds and Machines, 11, 483–502.
Bechtel, W., & Richardson, R. C. (1993). Discovering complexity: Decomposition and localization as strategies in scientific research. Princeton, NJ: Princeton University Press.
Beed, C., & Beed, C. (2000). Is the case for social science laws strengthening? Journal for the Theory of Social Behaviour, 30(2), 131–153.
Blau, P. M. (1977). A macrosociological theory of social structure. American Journal of Sociology, 83(1), 26–54.
Blau, P. M. (1983). Comments on the prospects for a nomothetic theory of social structure. Journal for the Theory of Social Behaviour, 13(3), 265–271.
Bunge, M. (2004). How does it work?: The search for explanatory mechanisms. Philosophy of the Social Sciences, 34(2), 182–210.
Carley, K. M., & Gasser, L. (1999). Computational organization theory. In G. Weiss (Ed.), Multiagent systems: A modern approach to distributed artificial intelligence (pp. 299–330). Cambridge: MIT Press.
Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. New York: Routledge.
Conte, R., Edmonds, B., Moss, S., & Sawyer, R. K. (2001). Sociology and social theory in agent based social simulation: A symposium. Computational and Mathematical Organization Theory, 7(3), 183–205.
Craver, C. (2001). Role functions, mechanisms and hierarchy. Philosophy of Science, 68, 31–55.
Craver, C. F. (2002). Interlevel experiments and multilevel mechanisms in the neuroscience of memory. Philosophy of Science, 69(Suppl), S83–S97.
David, N. (2012). Validating simulations. In B. Edmonds & R. Meyer (Eds.), Simulating social complexity: A handbook. Berlin: Springer-Verlag.
David, N., Fachada, N., & Rosa, A. C. (2017). Verifying and validating simulations. doi:https://doi.org/10.1007/978-3-319-66948-9_9.
Davidson, D. (1980). Essays on actions and events. New York: Oxford University Press.
Drennan, M. (2005). The human science of simulation: A robust hermeneutics for artificial societies. Journal of Artificial Societies and Social Simulation, 8(1). http://jasss.soc.surrey.ac.uk/8/1/3.html
Elster, J. (1989). Nuts and bolts for the social sciences. Cambridge: New York.
Elster, J. (1998). A plea for mechanism. In P. Hedström & R. Swedberg (Eds.), Social mechanisms: An analytical approach to social theory (pp. 45–73). Cambridge, UK: Cambridge University Press.
Fodor, J. A. (1974). Special sciences (or: The disunity of science as a working hypothesis). Synthese, 28, 97–115.
Giddens, A. (1984). The constitution of society: Outline of the theory of structuration. Berkeley, CA: University of California Press.
Gladwell, M. (2000). The tipping point. New York: Little, Brown.
Glennan, S. S. (1996). Mechanisms and the nature of causation. Erkenntnis, 44, 49–71.
Hedström, P. (2005). Dissecting the social: On the principles of analytic sociology. Cambridge, UK: Cambridge University Press.
Hedström, P., & Swedberg, R. (Eds.). (1998). Social mechanisms: An analytical approach to social theory. Cambridge, UK: Cambridge University Press.
Hempel, C. G. (1965). Aspects of scientific explanation and other essays in the philosophy of science. New York: Free Press.
Kincaid, H. (1990). Defending laws in the social sciences. Philosophy of the Social Sciences, 20(1), 56–83.
Little, D. (1991). Varieties of social explanation: An introduction to the philosophy of science. Boulder, CO: Westview Press.
Little, D. (1993). On the scope and limits of generalization in the social sciences. Synthese, 97(2), 183–207.
Little, D. (1998). Microfoundations, method and causation: On the philosophy of the social sciences. New Brunswick, NJ: Transaction Publishers.
Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67, 1–25.
Macy, M. W., & Skvoretz, J. (1998). The evolution of trust and cooperation between strangers: A computational model. American Sociological Review, 63, 638–660.
Markovsky, B. (1997). Building and testing multilevel theories. In J. Szmatka, J. Skvoretz, & J. Berger (Eds.), Status, network, and structure: Theory development in group processes (pp. 13–28). Stanford: Palo Alto, CA.
Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253.
McIntyre, L. C. (1996). Laws and explanation in the social sciences: Defending a science of human behavior. Boulder, CO: Westview.
Morelli, G. A., Rogoff, B., Oppenheim, D., & Goldsmith, D. (1992). Cultural variation in infants' sleeping arrangements: Questions of independence. Developmental Psychology, 28(4), 604–613.
Neumann, M. (2006, October 5–6). Emergence as an explanatory principle in artificial societies: Reflections on the bottom-up approach to social theory. In F. Squazzoni (Ed.), Epistemological aspects of computer simulation in the social sciences: Second international workshop, EPOS 2006, Brescia, Italy, revised selected and invited papers, Lecture notes in computer science (Vol. 5466, pp. 69–88). Berlin: Springer.
Ostrom, T. (1988). Computer simulation: The third symbol system. Journal of Experimental Social Psychology, 24, 381–392.
Salmon, W. (1971). Statistical explanation. In W. Salmon (Ed.), Statistical explanation and statistical relevance (pp. 29–87). Pittsburgh: University of Pittsburgh Press.
Salmon, W. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.
Salmon, W. (1994). Causality without counterfactuals. Philosophy of Science, 61, 297–312.
Salmon, W. (1997). Causality and explanation: A reply to two critiques. Philosophy of Science, 64, 461–477.
Sawyer, R. K. (2002). Nonreductive individualism, part 1: Supervenience and wild disjunction. Philosophy of the Social Sciences, 32(4), 537–559.
Sawyer, R. K. (2003a). Artificial societies: Multi agent systems and the micro-macro link in sociological theory. Sociological Methods and Research, 31(3), 37–75.
Sawyer, R. K. (2003b). Nonreductive individualism, part 2: Social causation. Philosophy of the Social Sciences, 33(2), 203–224.
Sawyer, R. K. (2004). The mechanisms of emergence. Philosophy of the Social Sciences, 34(2), 260–282.
Sawyer, R. K. (2005). Social emergence: Societies as complex systems. Cambridge: New York.
Sawyer, R. K. (2006). Explaining creativity: The science of human innovation. Oxford: New York.
Schmid, A. (2006, October 5–6). What does emerge in computer simulations? Simulation between epistemological and ontological emergence. In F. Squazzoni (Ed.), Epistemological aspects of computer simulation in the social sciences: Second international workshop, EPOS 2006, Brescia, Italy, revised selected and invited papers, Lecture notes in computer science (Vol. 5466, pp. 60–68). Berlin: Springer.
Stinchcombe, A. L. (1991). The conditions of fruitfulness of theorizing about mechanisms in social science. Philosophy of the Social Sciences, 21(3), 367–388.
Triandis, H. C. (1995). Individualism & collectivism. Boulder, CO: Westview Press.
Turner, J. H. (1993). Classical sociological theory: A positivist perspective. Chicago: Nelson-Hall.
Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Further Reading
Further Reading
Bechtel and Richardson (1993) provide a discussion of a range of philosophical issues related to the likely success of reductionist strategies in understanding and explaining complex systems, inspired by connectionist accounts of cognition, but relevant to complex systems at any level of analysis. Hedström (2005) makes a strong case for reductionist explanation of social systems, using mechanistic explanation and specifically multi-agent-based simulation in connection with empirical study.
For an examination of the philosophical accounts of mechanistic explanation and theories of emergence in sociology and philosophy, see Sawyer (2004). For an extensive review of historical and contemporary theories of emergence in the social sciences, primarily psychology and sociology, see Sawyer (2005). This advocates that sociology should be the science of social emergence. Conte et al. (2001) is a discussion between four different viewpoints specifically as they concern social simulation.
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Sawyer, R.K. (2017). Interpreting and Understanding Simulations: The Philosophy of Social Simulation. In: Edmonds, B., Meyer, R. (eds) Simulating Social Complexity. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-66948-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-66948-9_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66947-2
Online ISBN: 978-3-319-66948-9
eBook Packages: Computer ScienceComputer Science (R0)