Panel Discussion

Moving Social-Behavioral Modeling Forward

Published in: Social-Behavioral Modeling for Complex Systems, Chapter 33 (2019). doi: 10.1002/9781119485001.ch33

Posted on RAND.org on June 11, 2019

by Angela O'Mahony, Paul K. Davis, Scott Appling, Matthew E. Brashears, Erica Briscoe, Kathleen M. Carley, Joshua M. Epstein, Luke J. Matthews, Theodore P. Pavlic, William, Rand, Scott Neal Reilly, William B. Rouse, Samarth Swarup, Andreas Tolk, Raffaele Vardavas, Levent Yilmaz

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Contributors offered suggestions to improve multi-scale modeling that focused mainly on getting model substance right. This chapter is an edited but not iterated recounting of responses to questions that deal with simulation and emergence, how to relate models at different levels of resolution, and how to assure more humanness in agents. Contributors differed on whether simulations can generate true emergence but differed also on what true means. In simulating human behavior, multi-scale investigations are often necessary because, e.g. not enough empirical data is available to establish the true causal relationships at a single level. In many cases social-behavioral problems are complex and volatile and the environmental volatility is such that by the time the training sets are developed they are no longer useful and that it is unlikely that all information can be known and processed—at least in the time available.

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