抄録
High-order human cognition involves processing of abstract and categorically represented knowledge. Although it has been conventionally assumed that there is a single innate representation system in our mind, we view, on the basis of recent empirical and simulation studies, the representational system as a dynamic mechanism, capable of selecting a representation scheme that meets situational characteristics. The present paper introduces a framework for a cognitive model that integrates robust and flexible internal representation machinery. Our modeling framework flexibly learns to adjust its internal knowledge representation scheme using a meta-heuristic optimization method. Three simulation studies were conducted. The results showed that SUPERSET, our new model, successfully exhibited cognitive behaviors that are consistent with three main theories of the human internal representation system. Furthermore, a simulation study on social cognitive behaviors showed that the model was capable acquiring knowledge with high commonality, even for a category structure with numerous valid conceptualizations.
