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.
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Van Dyke Parunak, H., Brueckner, S., Downs, E.A., Sappelsa, L. (2013). Swarming Estimation of Realistic Mental Models. In: Giardini, F., Amblard, F. (eds) Multi-Agent-Based Simulation XIII. MABS 2012. Lecture Notes in Computer Science(), vol 7838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38859-0_4
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DOI: https://doi.org/10.1007/978-3-642-38859-0_4
Publisher Name: Springer, Berlin, Heidelberg
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