Exploring the Use of Cognitive Models in AI Applications Using the Stroop Effect

Charles Hannon and Diane J. Cook, University of Texas at Arlington, USA

Using a generalized adaptive framework for unified cognitive modeling, we replicate human performance on a standard Stroop task within an explanatory computational model of vision, language and higher order processing. Having shown the ability to generate similar results to its human counterpart on a Stroop Test evaluation, we discuss how a succession of similar tests on well-understood phenomena like the Stroop Effect can be used to refine a broader model of unified cognition which can then be used to improve general AI applications.


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