Meet Aileen, she may like walks in the park, could be fond of chocolate and those videos of people popping pimples. Honestly, you'll never know, as Aileen doesn't exist; she's another product of AI image generators. Aileen is the face of a new photo studio and modelling agency, one with a big difference – Deep Agency has no photographers, no locations and no real people. You simply put in your needs and out comes a realistic photo of a model, you can even upload yourself. For small agencies and marketing departments this could be a great app to use.

Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. In this paper, we explore how computational models of analogical processing can be brought into these architectures to enable concept acquisition from examples obtained interactively. We propose a new analogical concept memory for Soar that augments its current system of declarative long-term memories. We frame the problem of concept learning as embedded within the larger context of interactive task learning (ITL) and embodied language processing (ELP). We demonstrate that the analogical learning methods implemented in the proposed memory can quickly learn a diverse types of novel concepts that are useful not only in recognition of a concept in the environment but also in action selection. Our approach has been instantiated in an implemented cognitive system AILEEN and evaluated on a simulated robotic domain.