Characterizing an Analogical Concept Memory for Newellian Cognitive Architectures

We propose a new long-term declarative memory for Soar that leverages the computational models of analogical reasoning and generalization. We situate our research in interactive task learning (ITL) and embodied language processing (ELP). We demonstrate that the learning methods implemented in the proposed memory can quickly learn a diverse types of novel concepts that are useful in task execution. Our approach has been instantiated in an implemented hybrid AI system AILEEN and evaluated on a simulated robotic domain.