Skip to main content

Interpreting and Understanding Simulations: The Philosophy of Social Simulation

  • Chapter
  • First Online:
Simulating Social Complexity

Part of the book series: Understanding Complex Systems ((UCS))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  • Axelrod, R. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Bechtel, W. (2001). The compatibility of complex systems and reduction: A case analysis of memory research. Minds and Machines, 11, 483–502.

    Article  Google Scholar 

  • Bechtel, W., & Richardson, R. C. (1993). Discovering complexity: Decomposition and localization as strategies in scientific research. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Beed, C., & Beed, C. (2000). Is the case for social science laws strengthening? Journal for the Theory of Social Behaviour, 30(2), 131–153.

    Article  Google Scholar 

  • Blau, P. M. (1977). A macrosociological theory of social structure. American Journal of Sociology, 83(1), 26–54.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bunge, M. (2004). How does it work?: The search for explanatory mechanisms. Philosophy of the Social Sciences, 34(2), 182–210.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. New York: Routledge.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Craver, C. (2001). Role functions, mechanisms and hierarchy. Philosophy of Science, 68, 31–55.

    Article  Google Scholar 

  • Craver, C. F. (2002). Interlevel experiments and multilevel mechanisms in the neuroscience of memory. Philosophy of Science, 69(Suppl), S83–S97.

    Article  Google Scholar 

  • David, N. (2012). Validating simulations. In B. Edmonds & R. Meyer (Eds.), Simulating social complexity: A handbook. Berlin: Springer-Verlag.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Book  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • Fodor, J. A. (1974). Special sciences (or: The disunity of science as a working hypothesis). Synthese, 28, 97–115.

    Article  Google Scholar 

  • Giddens, A. (1984). The constitution of society: Outline of the theory of structuration. Berkeley, CA: University of California Press.

    Google Scholar 

  • Gladwell, M. (2000). The tipping point. New York: Little, Brown.

    Google Scholar 

  • Glennan, S. S. (1996). Mechanisms and the nature of causation. Erkenntnis, 44, 49–71.

    Article  Google Scholar 

  • Hedström, P. (2005). Dissecting the social: On the principles of analytic sociology. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Hedström, P., & Swedberg, R. (Eds.). (1998). Social mechanisms: An analytical approach to social theory. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Hempel, C. G. (1965). Aspects of scientific explanation and other essays in the philosophy of science. New York: Free Press.

    Google Scholar 

  • Kincaid, H. (1990). Defending laws in the social sciences. Philosophy of the Social Sciences, 20(1), 56–83.

    Article  Google Scholar 

  • Little, D. (1991). Varieties of social explanation: An introduction to the philosophy of science. Boulder, CO: Westview Press.

    Google Scholar 

  • Little, D. (1993). On the scope and limits of generalization in the social sciences. Synthese, 97(2), 183–207.

    Google Scholar 

  • Little, D. (1998). Microfoundations, method and causation: On the philosophy of the social sciences. New Brunswick, NJ: Transaction Publishers.

    Google Scholar 

  • Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67, 1–25.

    Article  MathSciNet  Google Scholar 

  • Macy, M. W., & Skvoretz, J. (1998). The evolution of trust and cooperation between strangers: A computational model. American Sociological Review, 63, 638–660.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253.

    Article  Google Scholar 

  • McIntyre, L. C. (1996). Laws and explanation in the social sciences: Defending a science of human behavior. Boulder, CO: Westview.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • Ostrom, T. (1988). Computer simulation: The third symbol system. Journal of Experimental Social Psychology, 24, 381–392.

    Article  Google Scholar 

  • Salmon, W. (1971). Statistical explanation. In W. Salmon (Ed.), Statistical explanation and statistical relevance (pp. 29–87). Pittsburgh: University of Pittsburgh Press.

    Chapter  Google Scholar 

  • Salmon, W. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Salmon, W. (1994). Causality without counterfactuals. Philosophy of Science, 61, 297–312.

    Article  MathSciNet  Google Scholar 

  • Salmon, W. (1997). Causality and explanation: A reply to two critiques. Philosophy of Science, 64, 461–477.

    Article  Google Scholar 

  • Sawyer, R. K. (2002). Nonreductive individualism, part 1: Supervenience and wild disjunction. Philosophy of the Social Sciences, 32(4), 537–559.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Sawyer, R. K. (2003b). Nonreductive individualism, part 2: Social causation. Philosophy of the Social Sciences, 33(2), 203–224.

    Article  Google Scholar 

  • Sawyer, R. K. (2004). The mechanisms of emergence. Philosophy of the Social Sciences, 34(2), 260–282.

    Article  Google Scholar 

  • Sawyer, R. K. (2005). Social emergence: Societies as complex systems. Cambridge: New York.

    Book  Google Scholar 

  • Sawyer, R. K. (2006). Explaining creativity: The science of human innovation. Oxford: New York.

    Google Scholar 

  • 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.

    Google Scholar 

  • Stinchcombe, A. L. (1991). The conditions of fruitfulness of theorizing about mechanisms in social science. Philosophy of the Social Sciences, 21(3), 367–388.

    Article  Google Scholar 

  • Triandis, H. C. (1995). Individualism & collectivism. Boulder, CO: Westview Press.

    Google Scholar 

  • Turner, J. H. (1993). Classical sociological theory: A positivist perspective. Chicago: Nelson-Hall.

    Google Scholar 

  • Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. Keith Sawyer .

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

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

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)

Publish with us

Policies and ethics