Reflections on Social Simulation and Complexity

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Abstract

After the involvement with a huge collection of case studies, where the experimentation may distinguish between luck and skill, our motivation was directed to see how agent-based modeling and model thinking were applied to general problem solving and case studies on complexity. Also, the development of models was directed to show the efficacy of diversity in attacking new scenarios and landscapes. And, even we avoided often Nassim Taleb’s mantra, “we tend to learn the overall precise and not the general”, the desire was to get realism (avoid embellished depiction of nature and behavior). This direction of research forced our attention upon the calibration of parameters, the validation, the use of mechanisms, the use of big data, and the activity of scaling up to check the plausibility of the outcomes.

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Coelho, H. (2019). Reflections on Social Simulation and Complexity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11805 LNAI, pp. 633–641). Springer Verlag. https://doi.org/10.1007/978-3-030-30244-3_52

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