SESSION 10: PARAMETER IDENTIFICATION AND OBJECTIVE
FUNCTIONS
Slides from class: Parameter Ident/Objective Functions (PDF)
Wickens, T. D. (1998). On the form of the retention function: Comment on Rubin and Wenzel (1996): A Quantitative Description of Retention. Psychological Review, 105, 379-386.
Code:
Number_Generators.f95
(used by all simulations)
Our MLP Classification model (Gaussian overlap vectors): Classify.f95
Probability of correct classification over training epochs:
Total activation to correct and incorrect output nodes over training epochs:
Modeling retention in our classification model over time: Retention.f95 (uses LuceÕs choice rule)
Varying the gamma parameter compared to human performance for our two groups:
Readings:
Pitt, M. A., & Myung, I. J. (2002). When a good fit can be bad. Trends in Cognitive Sciences, 6, 421-425.
Roberts, S., & Pashler, H. (2000). How persuasive is a good fit? A comment on theory testing. Psychological Review, 107, 358-367.