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Towards an Emergence-Driven Software Process for Agent-Based Simulation

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Multi-Agent-Based Simulation II (MABS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2581))

Abstract

In this paper we propose an emergence-driven software process for agent-based simulation that clarifies the traceability of micro and macro observations to micro and macro specifications in agent-based models. We use the concept of hyperstructures [1] to illustrate how micro and macro specifications interact in agent-based models, and show that the reductionism/ non-reductionism debate is important to understand the reliability of agent-based simulations. In particular, we show that the effort expended in the verification of agent-based simulations increases exponentially with the number of micro and macro specifications, and that the reliability assessment of non-anticipated results in simulation is in practice not possible. According to these results we claim to be impossible in practice to verify that an agent-based conceptual model has been implemented properly as a computational model, since we do not usually know what we want the output to be a priori. We thus advocate that the classic process of verification, validation and exploration of non-anticipated results is not reliable in agent-based simulation, and call into question the applicability of traditional software engineering methods to agent-based simulation.

Partially supported by FCT/PRAXIS XXI, Portugal, grant number BD/21595/99.

Partially supported by CNPq, Brazil, grant number 301041/95-4, and by project MAPPEL (PROTEM-CC, CNPq/NSF), grant number 680033/99-8.

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References

  1. Baas N.A. and Emmenche C. (1997). On Emergence and Explanation. In: Intellectica, 25, pp.67–83.

    Google Scholar 

  2. Cariani P. (1991). Emergence and Artificial Life. In: Artificial Life II, Addison Wesley, pp.775–797.

    Google Scholar 

  3. Castelfranchi C., Miceli M. and Cesta A. (1992). Dependence relations among autonomous agents, Proceedings of MAAMAW92, Elsevier Science, pp. 215–227.

    Google Scholar 

  4. Ciancarini P. and Wooldridge M. (eds), 2001. Agent-Oriented Software Engineering, Springer-Verlag, LNAI1957.

    Google Scholar 

  5. Conte R, Edmonds B., Moss S. and Sawyer R.K. (2001). Sociology and Social Theory in Agent Based Social Simulation:A Symposium. In Computational and Mathematical Organization Theory, 7(3), pp.183–205.

    Article  Google Scholar 

  6. Conte R. and Sichman J.S. (1995). DEPNET: How to benefit from social dependence, In: Journal of Mathematical Sociology, 20(2–3), 161–177.

    Article  Google Scholar 

  7. Cornelissen F., Jonker C.M. and Treur J. (2001). Compositional Verification of Knowledge-Based Systems: a Case Study for Diagnostic Reasoning. In Series in Defeasible Reasoning and Uncertainty Management Systems, vol.6, Kluwer Academic Publishers, pp. 65–82.

    MathSciNet  Google Scholar 

  8. David N., Sichman J.S. and Coelho H. (2001). Agent-Based Social Simulation with Coalitions in Social Reasoning, In Moss S. and Davidsson P., editors, Multi-Agent-Based Simulation, Springer Verlag, LNAI, v.1979, pp.244–265.

    Google Scholar 

  9. Davidsson P. (2002). Agent Based Social Simulation: A Computer Science View, In JASSS, vol.5, no.1, http://jasss.soc.surrey.ac.uk/5/1/7.html.

  10. Epstein J. and Axtell R. (1996). Growing Artificial Societies: Social Science from the Bottom Up, MIT press.

    Google Scholar 

  11. Gilbert N. and Troitzsch K. (1999). Simulation for the Social Scientist, Open University Press.

    Google Scholar 

  12. Langton C., Minar N., and Burkhart R., The Swarm Simulation System: A Tool for studying complex systems, http://www.swarm.org.

  13. Law A. and Kelton W.D. (1991). Simulating Modelling and Analysis, McGraw-Hill.

    Google Scholar 

  14. Lienz B. and Swanson E. (1980). Software Maintenance Management, Addison-Wesley.

    Google Scholar 

  15. McCabe T. and Butler W. (1989). Design Complexity Measurement and Testing, In: CACM, vol.32, no.12.

    Google Scholar 

  16. Mills D., Dyer M. and Linger R. (1987). Cleanroom software engineering, In: IEEE Software, vol.4, no.2.

    Google Scholar 

  17. Pressman R. (1994). Software Engineering: A Practitioner’s Approach, McGraw-Hill.

    Google Scholar 

  18. Sargent R.G. (1999). Validation and Verification of Simulation Models. In: Winter Simulation Conference, IEEE, Piscataway, NJ, 39–48.

    Google Scholar 

  19. Sommerville I. (1998). Software Engineering, Addison Wesley.

    Google Scholar 

  20. Troitzsch K.G., Brassel K, Mohring M. and Shumacher E. (1997). Can Agents Cover All the World?, In: Simulating Social Phenomena, Springer-Verlag, LNEMS 456, pp.55–72.

    Google Scholar 

  21. Marietto M.B., David N., Sichman J.S. and Coelho H. (2002). Requirements Analysis of Agent-Based Simulation Platforms: State of the Art and New Prospects. In this volume.

    Google Scholar 

  22. Sichman J.S. (1998). DEPINT: Dependence-based coalition formation in an open multiagent scenario, In Journal of Artificial Societies and Social Simulation, 1 (2), http://www.soc.survey.ac.uk/JASSS/1/2/3.html.

  23. Axtell R., Axelrod R., J.M. Epstein and M.D. Cohen (1996). Aligning Simulation Models: A Case Study and Results, Computational and Mathematical Organization Theory 1(2), pp. 123–141.

    Article  Google Scholar 

  24. DeMillo R., Lipton R. and Perlis A. (1979). Social Processes and proofs of theorems and programs, Communications of the ACM 22, 5 (May), 271–280.

    Article  Google Scholar 

  25. Antunes L., Nobrega L. and Coelho H. (2002). BVG choice in Axerold’s tribute model. In this volume.

    Google Scholar 

  26. Baas N.A. (1994). Emergence, Hierarchies and Hyperstructures. In Langton C. (eds), Artificial Life III, Santa Fe Studies in the Sciences of Complexity, Proceedings, Volume XVII, Addison-Wesley.

    Google Scholar 

  27. Sawyer R.K. (2001). Simulating Emergence and Downward Causation in Small Groups. In Moss S. and Davidsson P., editors, Multi-Agent-Based Simulation, Springer Verlag, LNAI, v.1979, pp.49–67.

    Google Scholar 

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David, N., Sichman, J.S., Coelho, H. (2003). Towards an Emergence-Driven Software Process for Agent-Based Simulation. In: Simão Sichman, J., Bousquet, F., Davidsson, P. (eds) Multi-Agent-Based Simulation II. MABS 2002. Lecture Notes in Computer Science(), vol 2581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36483-8_7

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  • DOI: https://doi.org/10.1007/3-540-36483-8_7

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