Relations between prototype, exemplar, and decision bound models of categorization
Journal of Mathematical Psychology
The Handbook of Brain Theory and Neural Networks
The Handbook of Brain Theory and Neural Networks
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Toward a descriptive cognitive model of human learning
Neurocomputing
A model of category learning with attention augmented simplistic prototype representation
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
A cognitive model of multi-objective multi-concept formation
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Modeling high-order human intelligence with intelligence of swarm
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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It is widely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of how categories are internally represented in our mind. Traditionally, it has been considered that there is a single innate internal representation system for categorical knowledge, such as Exemplars, Prototypes, or Rules. However, results of recent empirical and computational studies collectively suggest that the human internal representation system is apparently capable of exhibiting behaviors consistent with various types of internal representation schemes. We, then, hypothesized that humans' representational system as a dynamic mechanism, capable of selecting a representation scheme that meets situational characteristics, including complexities of category structure. The present paper introduces a framework for a cognitive model that integrates robust and flexible internal representation machinery. 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 of acquiring knowledge with high commonality, even for a category structure with numerous valid conceptualizations.