This chapter provides an introduction to the CHREST architecture of cognition and shows how this architecture can help develop a full theory of mind. After describing the main components and mechanisms of the architecture, we discuss several domains where it has already been successfully applied, such as in the psychology of expert behaviour, the acquisition of language by children, and the learning of multiple representations in physics. We highlight the characteristics of CHREST that enable it to account for empirical data, including self-organisation, an emphasis on cognitive limitations, the presence of a perception-learning cycle, and the use of naturalistic data as input for learning. We argue that some of these characteristics can help shed light on the hard questions facing theorists developing a full theory of mind, such as intuition, the acquisition and use of concepts, the link between cognition and emotions, and the role of embodiment.
The Role of Multiple Representations and Representational Fluency in Cryptography Education
