AI & SOCIETY

, Volume 27, Issue 4, pp 535–541 | Cite as

Wealth adjustment using a no-interest credit network in an artificial society

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Abstract

This paper discusses the possibility of wealth adjustment through a credit network. The discussed credit network in this paper is a kind of loaning with no interest rate (its value is zero). It explains the influence of existence or inexistence of a cooperation originated from the credit network on wealth distribution and adjustment in an artificial society. To show how the wealth may distribute, environment agents in terms of their obtained wealth have been classified into ten wealth categories; thus, the share of each category in terms of population has been determined. In addition, the survival of population in the environment has been studied. Findings and results show more balanced distribution of agents among the categories of wealth and higher survival of the population in the existence of the credit network. More over, the curve of population has fewer fluctuations. In other words, the population is more stable due to the ability of credit network in making more survival and stability in the population of environment in periods of time by providing the possibility of cooperation and wealth better distribution.

Keywords

Artificial society Sugarscape model Credit network Wealth distribution Wealth adjustment 

Notes

Acknowledgments

This research is supported by Roudehen branch of Islamic Azad University.

References

  1. Bar-Yam Y (1997) Dynamics of complex systems. New England Complex Systems Institute, Cambridge, MAMATHGoogle Scholar
  2. Buzzing PC (2003) VUSCAPE: communication and cooperation in evolving artificial societies, master’s thesis. Artificial Intelligence Department of Computer Science, Faculty of Sciences, Vrije University, Amsterdam, The NetherlandsGoogle Scholar
  3. Buzzing PC, Eiben AE, Schut M (2005) MC emerging communication and cooperation in evolving agent societies. J Artif Soc Soc Simul 8(1). http://jasss.soc.surrey.ac.uk/8/1/2.html
  4. Densmore O (2011) Sugarscape (2003 NetLogo community model). http://ccl.northwestern.edu/netlogo/models/community
  5. Epstein JM, Axtell R (1996) Growing artificial societies: social science from the bottom up. Brookings Institution Press, Washington DCGoogle Scholar
  6. Hales D (2001) Tag based co-operation in artificial societies, PhD thesis. Department of Computer Science, University of Essex, Colchester, EssexGoogle Scholar
  7. NetLogo Group (2011) NetLogo Software 4.0.4. Center for Connected Learning and Computer-Based Modeling. Northwestern University, Evanston/Chicago, IL, ReleasedGoogle Scholar
  8. Pfeifer R, Kunz H, Weber MM, Thomas D (2001) Artificial life. Institute for Informatik, Zurich University, ZurichGoogle Scholar
  9. Rahman A (2011) Application of artificial societies in analysis of social dynamic phenomena and complex processes. Iranian J Soc Res (in press)Google Scholar
  10. Rahman A, Setayeshi S (Nov 2006) Designing health development model in an artificial society through optimizing of disease distribution model between population. In: Proceedings of the international conference on telemedicine and e-health. Shahid Beheshti University of Medical Science and Health Services, TehranGoogle Scholar
  11. Rahman A, Setayeshi S (2007a) Evolution of social behavior in artificial society. In: Proceedings of the12th international CSI computer conference. Shahid Beheshti University, Faculty of Electrical and Computer Engineering, TehranGoogle Scholar
  12. Rahman A, Setayeshi S (2007b) The role of wealth distribution, inheritance and population control in social welfare: simulation of social welfare in artificial society. J Soc Welf 26:183–200Google Scholar
  13. Rahman A, Setayeshi S (2007c) Modeling of health destruction arising from spreading pollution. In: Proceedings of the 15th Iranian conference on electrical & computer engineering (ICEE 2007). Iran Telecom Research Center, TehranGoogle Scholar
  14. Rahman A, Setayeshi S (2008) Sugarscape model as a dynamic approach in analysis and optimization of social and economic complex systems. In: Proceeding of 2nd joint congress on fuzzy and intelligent systems. Malek Ashtar University of Technology, TehranGoogle Scholar
  15. Rahman A, Setayeshi S (2010) Artificial life. Roudehn Branch, Publication of Islamic Azad University, RoudehenGoogle Scholar
  16. Rahman A, Setayeshi S (in press) Complex systems analysis in artificial life based on sugarscape model. CSI J Comp Sci Eng (JCSE), Computer Society of Iran, TehranGoogle Scholar
  17. Rahman A, Setayeshi S, Shamsaei M (2007) An analysis to wealth distribution based on Sugarscape model in an artificial society. Int J Eng 20(3):211–224Google Scholar
  18. Rahman A, Setayeshi S, Shamsaei M (2008a) Health Monitoring in Artificial Life In the field of Contagious Diseases and Pollution. J Health Adm 11(31):27–38Google Scholar
  19. Rahman A, Setayeshi S, Shamsaei M (2008b) Optimization in complex systems using CA based Sugarscape method in artificial society. PhD thesis. Science and Research Branch, Islamic Azad University, TehranGoogle Scholar
  20. Rahman A, Setayeshi S, and Shamsaei M (2009a) Wealth adjustment in an artificial society, based on a Sugarscape model using one fifth of the wealth variable. Iran J Electr Comput Eng Iranian Research Institute for Electrical Engineering 8(1):35–40Google Scholar
  21. Rahman A, Setayeshi S, Shamsaei M (2009b) Wealth adjustment using a synergy between communication, cooperation, and one-fifth of wealth variables in an artificial society. Int J Artif Intell Soc 24(2):151–164Google Scholar
  22. Researchers of Leicester University (2009) The Sugarscape. The Center for Multidisciplinary Science. University of Leicester, http://www2.le.ac.uk/departments/interdisciplinary-science/research/the-sugarscape
  23. Toma T (2003) Communication in artificial society—effects of different communication protocols in an artificial environment. Master’s thesis. Artificial Intelligence Department of Computer Science, Faculty of Sciences, Vrije University, Amsterdam, The NetherlandsGoogle Scholar
  24. Weaver L (2009) Sugarscape. NetLogo user community model. http://ccl.northwestern.edu/netlogo/models/community/Sugarscape

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Department of Computer Engineering (Software Eng.), Faculty of EngineeringIslamic Azad University, Roudehen BranchRoudehenIran

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