Human-robot interaction is becoming an interesting area of research in
cognitive science, notably, for the study of social cognition. Interaction
theorists consider primary intersubjectivity a non-mentalist, pre-theoretical,
non-conceptual sort of processes that ground a certain level of communication
and understanding, and provide support to higher-level cognitive skills. We
argue this sort of low level cognitive interaction, where control is shared in
dyadic encounters, is susceptible of study with neural robots. Hence, in this
work we pursue three main objectives. Firstly, from the concept of active
inference we study primary intersubjectivity as a second person perspective
experience characterized by predictive engagement, where perception, cognition,
and action are accounted for an hermeneutic circle in dyadic interaction.
Secondly, we propose an open-source methodology named \textit{neural robotics
library} (NRL) for experimental human-robot interaction, and a demonstration
program for interacting in real-time with a virtual Cartesian robot (VCBot).
Lastly, through a study case, we discuss some ways human-robot (hybrid)
intersubjectivity can contribute to human science research, such as to the
fields of developmental psychology, educational technology, and cognitive
rehabilitation
