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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Acknowledgments
I am very indebted to my colleagues Carlos Lemos and João Balsa for the discussion of several themes of this paper, and during recent years. Social simulation and modeling is an area of AI research important to many fields in Portugal (and world wide), namely for the health care, where we need to be very careful. This research was funded by BioISI, FCT funding UID/MULTI04046/2019.
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Coelho, H. (2019). Reflections on Social Simulation and Complexity. In: Moura Oliveira, P., Novais, P., Reis, L. (eds) Progress in Artificial Intelligence. EPIA 2019. Lecture Notes in Computer Science(), vol 11805. Springer, Cham. https://doi.org/10.1007/978-3-030-30244-3_52
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