Cognitive architecture for human–robot interaction: Towards behavioural alignment

With increasingly competent robotic systems desired and required for social human–robot interaction comes the necessity for more complex means of control. Cognitive architectures (specifically the perspective where principles of structure and function are sought to account for multiple cognitive competencies) have only relatively recently been considered for application to this domain. In this paper, we describe one such set of architectural principles – activation dynamics over a developmental distributed associative substrate – and show how this enables an account of a fundamental competence for social cognition: multi-modal behavioural alignment. Data from real human–robot interactions is modelled using a computational system based on this set of principles to demonstrate how this competence can therefore be considered as embedded in wider cognitive processing. It is shown that the proposed system can model the behavioural characteristics of human subjects. While this study is a simulation using real interaction data, the results obtained validate the application of the proposed approach to this issue.