Skip to main content
Log in

Context in social simulation: why it can’t be wished away

  • SI: Epistemological Perspectives Simulation
  • Published:
Computational and Mathematical Organization Theory Aims and scope Submit manuscript

Abstract

Context is everywhere in the human social and cognitive spheres but it is often implicit and unnoticed. However, when one is involved in trying to understand and model the social and cognitive realms context becomes an important factor. This paper is an analysis of the role and effects of context on social simulation and a call for it to be squarely faced by the social simulation community. It briefly looks at some different kinds of context, and discussed the difficulty of talking about context, before looking at the “context heuristic” that seems to be used in human cognition. This allows for rich and fuzzy context recognition to be combined with crisp ‘foreground’ belief update and reasoning. Such a heuristic allows for causality to make sense, and limits the phenomena of causal spread—it is thus at the root of the modelling enterprise. This analysis is then applied to simulation modelling, considering the context of a simulation, and its ramifications, in particular, why generalisation is so hard.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Andrighetto G, Campennì M, Conte R, Cecconi F (2008) Conformity in multiple contexts: imitation vs norm recognition. In: World congress on social simulation 2008 (WCSS-08), George Mason University, Fairfax, USA

    Google Scholar 

  • Barwise J, Perry J (1983) Situations and attitudes. MIT Press, Cambridge

    Google Scholar 

  • Chattoe E (1998) Just how (un)realistic are evolutionary algorithms as representations of social processes? J Artif Soc Soc Simul 1(3):2. http://jasss.surrey.ac.uk/1/3/2.html

    Google Scholar 

  • Coser LA (1977) The sociology of Max Weber. Vintage Books, New York

    Google Scholar 

  • Deacon TW (1998) Symbolic species: the co-evolution of language and the brain. Norton, New York

    Google Scholar 

  • Edmonds B (1999a) The pragmatic roots of context. In: CONTEXT’99, Trento, Italy, September 1999. Lecture notes in artificial intelligence, vol 1688, pp 119–132

    Google Scholar 

  • Edmonds B (1999b) Capturing social embeddedness: a constructivist approach. Adapt Behav 7:323–348

    Article  Google Scholar 

  • Edmonds B (2002) Learning and exploiting context in agents. In: Proceedings of the 1st international joint conference on autonomous agents and multiagent systems (AAMAS), Bologna, Italy, July 2002. ACM, New York, pp 1231–1238

    Chapter  Google Scholar 

  • Edmonds B (2007) The practical modelling of context-dependent causal processes----a recasting of Robert Rosen’s thought. Chem Biodiv (special issue on Robert Rosen) 4(1):2386–2395

    Article  Google Scholar 

  • Edmonds B (2009) The nature of noise. In: Squazzoni F (ed) Epistemological aspects of computer simulation in the social sciences. Lecture notes in artificial intelligence, vol 5466, pp 169–182

    Chapter  Google Scholar 

  • Edmonds B (2010) Bootstrapping knowledge about social phenomena using simulation models. JASSS 13(1):8. http://jasss.soc.surrey.ac.uk/13/1/8.html

    Google Scholar 

  • Edmonds B (in press) Complexity and context-dependency. Found Sci

  • Edmonds B, Norling E (2007) Integrating learning and inference in multi-agent systems using cognitive context. In: Antunes L, Takadama K (eds) Multi-agent-based simulation. VII. Lecture notes in artificial intelligence, vol 4442, pp 142–155

    Chapter  Google Scholar 

  • Elliott CS, Hayward DM (1998) The expanding definition of framing and its particular impact on economic experimentation. J Socio-Econ 27(2):229–243

    Article  Google Scholar 

  • Entman RM (1993) Framing: towards clarification of a fractured paradigm. J Commun 43:51–58

    Article  Google Scholar 

  • Gärdenfors P (1997) The pragmatic role of modality in natural language. In: 20th Wittgenstein symposium, Kirchberg am Weshel, Lower Austria, Wittgenstein Society

    Google Scholar 

  • Gigerenzer G (1996) Rationality: Why social context matters. In: Baltes PB, Staudinger U (eds) Interactive minds: life-span perspectives on the social foundation of cognition. Cambridge University Press, Cambridge

    Google Scholar 

  • Gilbert N (2006) When does social simulation need cognitive models? In: Sun R (ed) Cognition and multi-agent interaction: from cognitive modeling to social simulation. Cambridge University Press, Cambridge, pp 428–432

    Google Scholar 

  • Goffman E (1974) Frame analysis: an essay on the organization of experience. Harvard University Press, Cambridge

    Google Scholar 

  • Greiner R, Darken C, Santoso NI (2001) Efficient reasoning. ACM Comput Surv 33(1):1–30

    Article  Google Scholar 

  • Hartmann S (2005) Models and stories in hadron physics. Preprint, http://philsci-archive.pitt.edu/id/eprint/2433 (accessed 2010-10-13)

  • Hayes P (1995) Contexts in context. In: Context in knowledge representation and natural language, AAAI Fall Symposium, November 1997. MIT Press, Cambridge

    Google Scholar 

  • Jolly A (2005) Social intelligence in primates and primatologists session. Invited talk AISB convention 2005 on social intelligence and interaction in animals, robots and agents, University of Hertfordshire, Hatfield, England, April 2005

  • Kaneko K (1990) Globally coupled chaos violates the law of large numbers but not the central-limit theorem. Phys Rev Lett 65:1391–1394

    Article  Google Scholar 

  • Kokinov B, Grinberg M (2001) Simulating context effects in problem solving with AMBR. In: Akman V, Bouquet P, Thomason R, Young RA (eds) Modelling and using context, vol 2116. Springer, Berlin, pp 221–234

    Chapter  Google Scholar 

  • Kuhn T (1966) The structure of scientific revolutions. University of Chicago Press, Chicago

    Google Scholar 

  • McCarthy J, Hayes PJ (1969) Some philosophical problems from the standpoint of artificial intelligence. Mach Intel 4:463–502

    Google Scholar 

  • McCarthy J (1971) Generality in artificial-intelligence—Turing award lecture. Commun ACM 30(12):1030–1035

    Article  Google Scholar 

  • McGilchrist I (2010) The master and his emissary: the divided brain and the making of the western world. Yale Univ. Press, New Haven

    Google Scholar 

  • Nelson TE, Oxley ZM, Clawson RA (1997) Towards a psychological of framing effects. Polit Behav 19(3):221–246

    Article  Google Scholar 

  • Pearl J (2000) Causality. Cambridge University Press, Cambridge

    Google Scholar 

  • Polanyi M (1966) The tacit dimension. Doubleday

  • Schatz J, Craft S, Koby M, DeBaun MR (2004) Asymmetries in visual-spatial processing following childhood stroke. Neuropsychology 18:340–352

    Article  Google Scholar 

  • Schlosser A, Voss M, Brückner L (2005) On the simulation of global reputation systems. J Artif Soc Soc Simul 9(1):4. http://jasss.soc.surrey.ac.uk/9/1/4.html

    Google Scholar 

  • Shafir E, Simonson I, Tversky A (1993) Reason-based choice. Cognition 49(1–2):11–36

    Article  Google Scholar 

  • Schelling TC (1969) Models of segregation. Am Econ Rev 59(2):488–493

    Google Scholar 

  • Schelling TC (1971) Dynamic models of segregation. J Math Sociol 1:143–186

    Article  Google Scholar 

  • Terán O (2004) Understanding MABS and social simulation: switching between languages in a hierarchy of levels. J Artif Soc Soc Simul 7(4):5. http://jasss.soc.surrey.ac.uk/7/4/5.html

    Google Scholar 

  • Tversky A, Kahneman D (1981) The framing of decisions and the psychology of choice. Science 211(4481):453–458

    Article  Google Scholar 

  • Tykhonov D, Jonker C, Meijer S, Verwaart T (2008) Agent-based simulation of the trust and tracing game for supply chains and networks. J Artif Soc Soc Simul 11(3):1. http://jasss.soc.surrey.ac.uk/11/3/1.html

    Google Scholar 

  • Volberg G, Hubner R (2004) On the role of response conflicts and stimulus position for hemispheric differences in global/local processing: an ERP study. Neuropsychologia 42:1805–1813

    Article  Google Scholar 

  • Wheeler M, Clark A (1999) Genic representation: reconciling content and causal complexity. Br J Philos Sci 50(1):103–135

    Article  Google Scholar 

  • Zadrozny W (1997) A pragmatic approach to context. In: Context in knowledge representation and natural language, AAAI fall symposium, November 1997. MIT Press, Cambridge

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bruce Edmonds.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Edmonds, B. Context in social simulation: why it can’t be wished away. Comput Math Organ Theory 18, 5–21 (2012). https://doi.org/10.1007/s10588-011-9100-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10588-011-9100-z

Keywords

Navigation