About this Research Topic
Since the topic deals with predictions of intentions, it lends itself well to efforts in computational modelling. Relevant work addresses (1) predictive explanations of human performance in intention understanding from observation, (2) accounts – including information theoretic approaches – of how social signals can be used in identification and prediction of intentions and (3) accounts of how such mechanisms can tie in with, for example, research on Theory of Mind (ToM).
A particular application for research in this area is in the field of robotics, particularly in human robot interaction (although the concept can be extended to interaction with other machines), for example involving service robotics, socially assistive robots (SAR) or robot assisted therapy (RAT). Such robots can benefit from algorithms that directly predict likely intentions of humans. These can be informed from human studies (for instance on the use of social signals) but, since robots have limited sensory and analytical abilities compared to humans, particular care needs to be given to how results on human strategies (or models thereof) can be translated onto robots. Equally, purely robotic strategies to achieve such predictions from the observation of humans (or indeed other robots) can be developed and compared to human approaches.
Conversely, designing robots whose social signals are particularly intuitive to humans is also relevant. Research in this direction can profit from an understanding of what social signals humans process when observing a scene.
Finally, a highly relevant but to date relatively unexplored area is that of endowing robots with a ToM tailored to the humans (or robots) they interact with. Here, a particular interest is which observable variables are most conducive to/can be used in the creation and/or improvement of such mechanisms.
The present topic is aimed at state of the art research which addresses research into social signals either (a) from a behavioural, psychological and neuroscientific perspective (b) through computational models (c) with robotic applications. Interdisciplinary papers covering two or more of these are especially encouraged. Papers should further the understanding of the use of social signals in human interactions and/or address applications in human-machine interaction. Papers on computational models in particular therefore should be careful to make their relevance to such applications clear.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.