Skip to main content

Agent-Based Modeling of Social Complex Systems

  • Conference paper
Current Topics in Artificial Intelligence (CAEPIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4177))

Included in the following conference series:

  • 876 Accesses

Abstract

This thesis proposal aims to provide a new approach to the study of complex adaptive systems in social sciences through a methodological framework for modeling and simulating these systems like artificial societies. Agent based modeling (ABM) is well fitted for the study of social systems as it focuses on how local interactions among agents generate emergent larger and global social structures and patterns of behavior. The issues addressed by our framework are presented as well as its most important components.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Axelrod, R.: Advancing the Art of Simulation in the Social Sciences. In: Conte, R., et al. (eds.) PLILP 1990. Lecture Notes in Economics and Mathematical Systems, vol. 456, pp. 21–40. Berlin Springer, Heidelberg (1997)

    Google Scholar 

  2. Axtell, R.: Why Agents? On the Varied Motivations for Agent Computing in the Social Sciences, in Working Paper No. 17, center on Social and Economic Dynamics, The Brookings Institution, Washington, DC (2000)

    Google Scholar 

  3. Coleman, J.C. (ed.): Foundations of Social Theory. ed. M.H.U.P. Cambridge, Harvard University Press, Cambridge, MA (1990)

    Google Scholar 

  4. Drogoul, A., Vanbergue, D., Meurisse, T.: Multi-agent Based Simulation: Where Are the Agents? In: Sichman, J.S., Bousquet, F., Davidsson, P., et al. (eds.) MABS 2002. LNCS (LNAI), vol. 2581, pp. 1–15. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  5. Epstein, J.M., Axtell, R.: Growing artificial societies: social science from the bottom up. In: Complex adaptive systems, Brookings Institution Press, Washington, D.C (1996)

    Google Scholar 

  6. Gilbert, N., Troitzsch, K.G.: Simulation for the Social Scientist. Open University Press, Buckingham, U.K (1996)

    Google Scholar 

  7. Pavón, J., Gómez-Sanz, J.: Agent Oriented Software Engineering with INGENIAS. In: Mařík, V., Müller, J.P., Pěchouček, M., et al. (eds.) CEEMAS 2003. LNCS (LNAI), vol. 2691, pp. 394–403. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  8. Sansores, C., Pavón, J.: Agent-Based Simulation Replication: a Model Driven Architecture Approach. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H., et al. (eds.) MICAI 2005. LNCS (LNAI), vol. 3789, pp. 244–256. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  9. Sansores, C., Pavón, J., Gómez-Sanz, J.: Visual Modeling for Complex Agent-Based Simulation Systems. In: Sichman, J.S., Antunes, L., et al. (eds.) MABS 2005. LNCS (LNAI), vol. 3891, pp. 174–189. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sansores, C., Pavón, J. (2006). Agent-Based Modeling of Social Complex Systems. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_11

Download citation

  • DOI: https://doi.org/10.1007/11881216_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45914-9

  • Online ISBN: 978-3-540-45915-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics