A common-sense conceptual categorization system integrating heterogeneous proxytypes and the dual process of reasoning

In this article we present DUAL-PECCS, an integrated Knowledge Representation system aimed at extending artificial capabilities in tasks such as conceptual categorization. It relies on two different sorts of cognitively inspired common-sense reasoning: prototypical reasoning and exemplars-based reasoning. Furthermore, it is grounded on the theoretical tenets coming from the dual process theory of the mind, and on the hypothesis of heterogeneous proxytypes, developed in the area of the biologically inspired cognitive architectures (BICA). The system has been integrated into the ACT-R cognitive architecture, and experimentally assessed in a conceptual categorization task, where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies. Compared to human-level categorization, the obtained results suggest that our proposal can be helpful in extending the representational and reasoning conceptual capabilities of standard cognitive artificial systems.