  Despite the recent advancement in the social robotic field, important
limitations restrain its progress and delay the application of robots in
everyday scenarios. In the present paper, we propose to develop computational
models inspired by our knowledge of human infants' social adaptive abilities.
We believe this may provide solutions at an architectural level to overcome the
limits of current systems. Specifically, we present the functional advantages
that adaptive Theory of Mind (ToM) systems would support in robotics (i.e.,
mentalizing for belief understanding, proactivity and preparation, active
perception and learning) and contextualize them in practical applications. We
review current computational models mainly based on the simulation and
teleological theories, and robotic implementations to identify the limitations
of ToM functions in current robotic architectures and suggest a possible future
developmental pathway. Finally, we propose future studies to create innovative
computational models integrating the properties of the simulation and
teleological approaches for an improved adaptive ToM ability in robots with the
aim of enhancing human-robot interactions and permitting the application of
robots in unexplored environments, such as disasters and construction sites. To
achieve this goal, we suggest directing future research towards the modern
cross-talk between the fields of robotics and developmental psychology.
