Visible to the public Modeling the Concentration Game with ACT-R

TitleModeling the Concentration Game with ACT-R
Publication TypeConference Paper
Year of Publication2013
AuthorsTitus Barik, Arpan Chakraborty, Brent Harrison, David L. Roberts, Robert St. Amant
Conference NameThe 12th International Conference on Cognitive Modeling
KeywordsLeveraging the Effects of Cognitive Function on Input Device Analytics to Improve Security

This paper describes the development of subsymbolic ACT-R models for the Concentration game. Performance data is taken from an experiment in which participants played the game un- der two conditions: minimizing the number of mismatches/ turns during a game, and minimizing the time to complete a game. Conflict resolution and parameter tuning are used to implement an accuracy model and a speed model that capture the differences for the two conditions. Visual attention drives exploration of the game board in the models. Modeling re- sults are generally consistent with human performance, though some systematic differences can be seen. Modeling decisions, model limitations, and open issues are discussed.

Citation Keynode-18972
Refereed DesignationUnknown