Trait Inference on Cognitive Model of Curiosity: Relationship between Perceived Intelligence and Levels of Processing

Cognitive models are used as simulators that derive external behavior from assumed internal states. As a tool for linking external behavior with internal causes, cognitive models can be used to examine human trait inference on others. While fundamental attribution errors are identified in social psychology, the specific factors remain unclear. By employing detailed cognitive models to specify internal states, it is possible to deepen our understanding of human inference on internal processes. In this study, we utilized the ACT-R cognitive architecture to construct such internal states and externalized behaviors. We also focused on 'curiosity' as an individual trait emphasized in real society to evaluate individuals. We developed a visualizer for the behavior of multiple models of curiosity and conducted subjective evaluations with participants recruited from a Japanese crowdsourcing site. As a result, we observed differences in inferred traits among models, although the specific patterns were not consistently aligned with the model assumptions. Additional analysis revealed that participants' inferences were more influenced by observable behavior patterns rather than internal processes, indicating a deficit in human attribution as suggested by the tradition of social psychology.