Swarming estimation of realistic mental models

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Abstract

Researchers have explored many formalisms to model how people think about their world. We describe an application that requires modeling how people forecast events in the real world. The naïve assumption is that they use formalisms that model how the world actually evolves. These formalisms are at variance with empirical psychological results. We present a more realistic alternative, the Narrative Space Model (NSM), describe a swarming agent algorithm to fit its parameters from observed data, and present some early results. © 2013 Springer-Verlag.

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Van Dyke Parunak, H., Brueckner, S., Downs, E. A., & Sappelsa, L. (2013). Swarming estimation of realistic mental models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7838 LNAI, pp. 43–55). https://doi.org/10.1007/978-3-642-38859-0_4

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