PCSinR: Parallel Constraint Satisfaction Networks in R
Parallel Constraint Satisfaction (PCS) models are an increasingly
common class of models in Psychology, with applications to reading and word
recognition (McClelland & Rumelhart, 1981), judgment and decision making
(Glöckner & Betsch, 2008; Glöckner, Hilbig, & Jekel, 2014), and several
other fields (e.g. Read, Vanman, & Miller, 1997). In each of these fields,
they provide a quantitative model of psychological phenomena, with precise
predictions regarding choice probabilities, decision times, and often the degree
of confidence. This package provides the necessary functions to create and
simulate basic Parallel Constraint Satisfaction networks within R.
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