Abstract
Experimental methodologies are harder to apply when selfmotivated agents are involved, especially when the issue of decision gains its due relevance in their model. Traditional experimentation has to give way to exploratory simulation, to bring insights into the design issues, not only of the agents, but of the experiment as well. The role of its designer cannot be ignored, at the risk of achieving only obvious, predictable conclusions. We propose to bring the designer into the experiment. We use the findings of extensive experimentation to compare current experimental methodologies in what concerns evaluation.
Longer version in Lindemann, Moldt, Paolucci and Yu,International Workshop on Regulated Agent-Based Social Systems: Theory and Applications (RASTA ’02), Universität Hamburg, FBI-HH-M-318/02, July 2002.
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References
Robert Axelrod. A model of the emergence of new political actors. In Artificial Societies — The Computer Simulation of Social Life. UCL Press, 1995.
Robert Axelrod. Advancing the art of simulation in the social sciences. In Simulating Social Phenomena, volume 456 of LNEMS. Springer, 1997.
Cristiano Castelfranchi. Guarantees for autonomy in cognitive agent architecture. In Intelligent Agents: agent theories, architectures, and languages, Proc. of ATAL’94, volume 890 of LNAI. Springer, 1995.
Cristiano Castelfranchi. The theory of social functions: challenges for computational social science and multi-agent learning. Journal of Cognitive Systems Research, 2, 2001.
John L. Casti. Would-be business worlds. Complexity, 6(2), 2001.
Paul R. Cohen. A survey of the eighth national conf. on AI: Pulling together or pulling apart? AI Magazine, 12(1):16–41, 1991.
Paul R. Cohen. Empirical Methods for AI. The MIT Press, 1995.
Rosaria Conte and Nigel Gilbert. Introduction: computer simulation for social theory. In Artificial Societies: the computer simulation of social life. UCL Press, 1995.
António Damásio. Descartes’ error. Putnam’s sons, New York, 1994.
Nigel Gilbert. Models, processes and algorithms: Towards a simulation toolkit. In Tools and Techniques for Social Science Simulation. Physica-Verlag, 2000.
Nigel Gilbert and Jim Doran, editors. Simulating Societies: the computer simulation of social phenomena. UCL Press, London, 1994.
David Hales. Tag Based Co-operation in Artificial Societies. PhD thesis, Univ. Essex, 2001.
Herbert A. Simon. A behavioral model of rational choice. Quarterly Journal of Economics, 69:99–118, Feb. 1955.
Klaus G. Troitzsch. Social science simulation — origins, prospects, purposes. In Simulating Social Phenomena, volume 456 of LNEMS. Springer, 1997.
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Antunes, L., Coelho, H. (2002). Towards a Methodology for Experiments with Autonomous Agents. In: Bittencourt, G., Ramalho, G.L. (eds) Advances in Artificial Intelligence. SBIA 2002. Lecture Notes in Computer Science(), vol 2507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36127-8_9
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DOI: https://doi.org/10.1007/3-540-36127-8_9
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