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Building an Artificial Primitive Human Society: An Agent-Based Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9372))

Abstract

The model presented here is mainly concerned with building an artificial society from the bottom-up by specifying their basic social structural elements and institutional meta-roles based on the CKSW (Commander, Knowledge, Skill, Worker) societal meta-model. In this paper our focus is to introduce different types of interactions and outline the degree to which they affect the sustainability of the modeled artificial society. The main motivation is to develop a model that can show institutional changes with minimum set of externally defined triggers to drive changes at the micro level.

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Notes

  1. 1.

    They do so in order to create more links and thus increasing their chance of finding mate.

  2. 2.

    High level of aggression in combinations with low altruism and high hunger level drive stealing behaviour.

References

  1. Gilbert, N., Troitzsch, K.: Simulation For The Social Scientist. McGraw-Hill International, New York (2005)

    Google Scholar 

  2. Edmonds, B., Lucas, P., Rouchier, J., Taylor, R.: Human Societies: Understanding Observed Social Phenomena. In: Edmonds, B., Meyer, R. (eds.) Simulating Social Complexity, pp. 709–748. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  3. Tesfatsion, L.: Agent-based computational economics: growing economies from the bottom up. Artif. Life 8, 55–82 (2002)

    Article  Google Scholar 

  4. Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2007)

    Google Scholar 

  5. Epstein, J.M., Axtell, R.L.: Growing Artificial Societies Social Science from the Bottom Up. The MIT Press, Cambridge (1994)

    Google Scholar 

  6. Gooding, T.: Modelling society’s evolutionary forces. J. Artif. Soc. Soc. Simul. 14 (2014)

    Google Scholar 

  7. Gotts, N.M., Polhill, J.G., Law, A.N.R.: Agent-based simulation in the study of social dilemmas. Artif. Intell. Rev. 19, 3–92 (2003)

    Article  Google Scholar 

  8. Vanhée, L., Ferber, J., Dignum, F.: Agent-based evolving societies. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems. pp. 1241–1242. International Foundation for Autonomous Agents and Multiagent Systems (2013)

    Google Scholar 

  9. Jahanbazi, M., Frantz, C., Purvis, M., Purvis, M., Nowostawski, M.: Agent-Based Modelling of Primitive Human Communities. Intelligent Agent Technology, Warsaw (2014)

    Google Scholar 

  10. Younger, S.: Leadership, violence, and warfare in small societies. J. Artif. Soc. Soc. Simul. 14 (2011)

    Google Scholar 

  11. Axtell, R.L., Epstein, J.M., Dean, J.S., Gumerman, G.J., Swedlund, A.C., Harburger, J., Chakravarty, S., Hammond, R., Parker, J., Parker, M.: Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proc. Natl. Acad. Sci. US Am. 99(3), 7275–7279 (2002)

    Article  Google Scholar 

  12. Billari, F.C., Ongaro, F., Prskawetz, A.: Introduction: agent-based computational demography. In: Billari, F.C., Prskawetz, A. (eds.) Agent-Based Computational Demography, pp. 1–17. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  13. Hammond, R.A., Axelrod, R.: The evolution of ethnocentrism. J. Confl. Resolut. 50, 926–936 (2006)

    Article  Google Scholar 

  14. Macmillan, W., Huang, H.Q.: An agent-based simulation model of a primitive agricultural society. Geoforum 39, 643–658 (2008)

    Article  Google Scholar 

  15. Huang, H.Q., Macmillan, W.: A generative bottom-up approach to the understanding of the development of rural societies. Agrifood Res. Rep. 68, 296–312 (2005)

    Google Scholar 

  16. Ewert, U.C., Roehl, M., Uhrmacher, A.M.: Hunger and market dynamics in pre-modern communities: insights into the effects of market intervention from a multi-agent model. Hist. Soc. Res. Sozialforsch. 32, 122–150 (2007)

    Google Scholar 

  17. Purvis, M.K., Purvis, M.A.: Institutional expertise in the Service-Dominant Logic: Knowing how and knowing what. J. Mark. Manag. 28, 1626–1641 (2012)

    Article  Google Scholar 

  18. Purvis, M., Purvis, M., Frantz, C.: CKSW: a folk-sociological meta-model for agent-based modelling. In: Social.Path Workshop (2014)

    Google Scholar 

  19. Simon, H.A.: A behavioral model of rational choice. Q. J. Econ. 69, 99–118 (1955)

    Article  Google Scholar 

  20. Gouldner, A.W.: The norm of reciprocity: a preliminary statement. Am. Sociol. Rev. 25, 161–178 (1960)

    Article  Google Scholar 

  21. Francesco, G.: Reciprocity: Weak or strong? what punishment experiments do (and do not) demonstrate. Behav. Brain Sci. 35, 1–15 (2012)

    Article  Google Scholar 

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Correspondence to Marzieh Jahanbazi .

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Jahanbazi, M., Frantz, C., Purvis, M., Purvis, M. (2015). Building an Artificial Primitive Human Society: An Agent-Based Approach. In: Ghose, A., Oren, N., Telang, P., Thangarajah, J. (eds) Coordination, Organizations, Institutions, and Norms in Agent Systems X. COIN 2014. Lecture Notes in Computer Science(), vol 9372. Springer, Cham. https://doi.org/10.1007/978-3-319-25420-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-25420-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25419-7

  • Online ISBN: 978-3-319-25420-3

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