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  "Title": "Parallel Constraint Satisfaction Networks in R",
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  "Description": "Parallel Constraint Satisfaction (PCS) models are an\nincreasingly common class of models in Psychology, with\napplications to reading and word recognition (McClelland &\nRumelhart, 1981; \\doi{10.1037/0033-295X.88.5.375}), judgment\nand decision making (Glöckner & Betsch, 2008\n\\doi{10.1017/S1930297500002424}; Glöckner, Hilbig, & Jekel,\n2014 \\doi{10.1016/j.cognition.2014.08.017}), and several other\nfields. In each of these fields, they provide a quantitative\nmodel of psychological phenomena, with precise predictions\nregarding choice probabilities, decision times, and often the\ndegree of confidence. This package provides the necessary\nfunctions to create and simulate basic Parallel Constraint\nSatisfaction networks within R.",
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        "PCSinR"
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