IJE TRANSACTIONS B: Applications Vol. 20, No. 3 (December 2007) 211-224   

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Arash Rahman

Department of Computer, Faculty of Engineering
Science and Research Branch, Islamic Azad University
Tehran, Iran

Saeed Setayeshi* and Mojtaba Shamsaei Zafarghandi

Faculty of Nuclear Engineering and Physics, Amirkabir University of Technology
Tehran, Iran
setayesh@aut.ac.ir - pysham@aut.ac.ir

*Corresponding Author

( Received: August 14, 2007 – Accepted in Revised Form: November 22, 2007 )

Abstract     In this paper an artificial society is being assumed as a multi agents system. A sugarscape model consisting of a cellular landscape of resources is used to form an interaction among the agents of the population. In the model, agents find the resources to survive. They are supposed to move and search and because of this movement, an evolutionary social behavior will develope. From model analysis view point this behavior should be parameterized and also optimized. To analyze the said assumption, each agent should gather and store as much sugar as possible to create an asset for itself. Hence, From the simulation result, the population be categorized based on the asset. In the society, wealth may be allocated based on the asset, gathered by the agents. The percentage of population who will possesses some percentage of the wealth is specified. The simulation shows that in an artificial life, it is possible to use the sugarscape model to optimize the behavior of a society, and the parameters of the model are predictable as well.  


Keywords    Artificial Life, Artificial Society, Sugarscape Model, Agent Based Modeling, Wealth Distribution



1. Buzzing, P., “VUSCAPE: Communication and Cooperation in Evolving Artificial Societies”, Master's Thesis, Artificial Intelligence Department of Computer Science, Faculty of Sciences, Vrije University, Amsterdam, The Netherlands, (2003).

2. Epstein, J. M. and Axtell R., “Growing Artificial Societies: Social Science from the Bottom Up”, Brookings Institution Press, Washington DC, U. S. A., (1996).

3. Pfeifer, R., Kunz, H., Weber M.M., Thomas D., “Artificial Life”, Institute for Informatics, Zurich University, Germany, (June 2001).

4. Zonemat Kermani, N., Setayeshi, S. and Teshnelab, M., “Implementation of Communication's Effect in Artificial Life and Effect of Evolutionary Functions in It”, Master's Thesis, Department of Computer Engineering, Faculty of Technical and Engineering, Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran, (2003).

5. Rahman, A. and Setayeshi, S., “Evolution of Social Behavior in Artificial Society”, Proceedings of the12th International CSI Computer Conference, Shahid Beheshti University, Faculty of Electrical and Computer Engineering, Tehran, Iran, (2007), 1219-1227.

6. Rahman, A. and Setayeshi, S., “Modeling of Health Destruction Arising from Spreading Pollution”, Proceedings of the 15th Iranian Conference on Electrical and Computer Engineering (ICEE 2007), (Biomedical Engineering Proceeding), Iran Telecom Research Center, Tehran, Iran, (2007), 91-97.

7. Rahman, A. and Setayeshi, S., “Implementation of AIDS Disease and HIV + Virus Distribution Model In an Artificial Society as a computation Approach to Establish the Electronic Health”, Proceedings of the First Conference on Study of IT Development Approach in Iranian Medical Sciences Universities, Shahid Beheshti University of Medical Science and Health Services, Tehran, Iran, (2007).

8. Rahman, A. and Setayeshi, S., “Designing Health Development Model in an Artificial Society through Optimizing of Disease Distribution Model between Population”, Proceedings of the International Conference on Telemedicine and e-Health, Shahid Beheshti University of Medical Science and Health Services, Tehran, Iran, (November 2006).

9. Rahman, A. and Setayeshi, S., “Complex Systems Analysis in Artificial Life based on Sugarscape Model”, Submitted to CSI Journal on Computer Science and Engineering, Tehran, Iran, (2006).

10. Toma, T., “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 Netherlands, (2003).

11. Bar-Yam, Y., “Dynamics of Complex Systems”, New England Complex Systems Institute, UK, (1997).

12. Axelrod, R., “The Convergence and Stability of Cultures: Local Convergence and Global Polarization”, SFI Working Paper 95-30-028, Sanata Fe, N. M.: Sanata Fe Institute, U. S. A., (1995).

13. Axelrod, R., “The Evolution of Co-operation”, New York, U.S.A., (1980).

14. Baptista, D., Torres, M. and Moreno, J. A., “Evolution of Social Behavior in Simulated Societies”, Proceedings World Multiconference on Systemics, Cybernetics and Informatics SCI’2000, Vol. X, (2000), 5-12.

15. Dascalu, M., Franti, E. and Stefan, G., “Modeling Production with Artificial Societies: the Emergence of Social Structure”, Acri'98-Proceedings of the Third Conference on Cellular Automata for Research and Industry, Springer-Verlag, Trieste, Italy, (1998).

16. Hales, D., “Memetic Engineering and Culture Evolution”, In Knowledge Management, Organizational Intelligence and Learning, and Complexity, (Ed. L. Douglas Kiel), in Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO, Eolss Publishers, Oxford, UK, (2004).

17. Hales, D., “Tag Based Co-operation in Artificial Societies”, Ph. D. Thesis, Department of Computer Science, University of Essex, UK, (2001).

18. Hales, D., “Selfish Memes and Selfless Agents, Altruism in the SwapShop”, Proceedings of the 3rd International Conference on Multi-Agent Systems, IEEE Computer Society, California, U.S.A., (1998).

19. Hales, D., “Stereotyping, Groups and Cultural Evolution: A Case of Second Order Emergence?”, Lecture Notes in Computer Science, Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation, Springer-Verlag, London, UK, Vol. 1534, (1998).

20. Hales D., “An Open Mind is Not an Empty Mind, Experiments in the Meta- Noosphere”, Journal of Artificial Society and Social Simulation, UK, Vol. 1, No. 4, (1998).

21. Gizzi, M., Vail, R. and Lairson, T., “Wealth Distribution Project”, Mesa State College, Center for Agent-Based Modeling, Evanston/Chicago, U. S. A., (2003).

22. NetLogo, Group, “NetLogo 3. 1. 3 Software, Center for Connected Learning and Computer-Based Modeling”, Northwestern University, Evanston, IL, U. S. A., (2006).

23. Rahman, A. and Setayeshi, S., “The Role of Wealth Distribution, Inheritance and Population Control in Social Welfare: Simulation of Social Welfare in Artificial Society”, Institute of Social Welfare Research, University of Social Welfare and Rehabilitation Sciences, Journal of Social Welfare, Tehran, Iran, Vol. 26, (2007).

24. Chattoe, E. and Gilbert, N., “A simulation of budgetary decision-making based on interview data”, Proceedings of the Third Symposium on Simulating Societies, Boca Raton, Florida, U. S. A., (1995).

25. Gilbert, N. and Conte, R., “Emergence in social simulation”, Artificial Societies London UCL Press, UK, (1995), 144-156.

26. Langlois, A. and Phipps, M., “Automates cellulaires application a la simulation urbaine”, HERMES, Paris, French, (1997).

27. Michalewicz, Z., “Genetic Algorithms + Data Structures = Evolution Programs”, Springer-Verlag, Second Edition, New York, U. S. A., (1994).

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