Intrinsically Motivated Autonomy in Human-Robot Interaction: Human Perception of Predictive Information in Robots

  • Marcus M. ScheunemannEmail author
  • Christoph Salge
  • Kerstin Dautenhahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11649)


In this paper we present a fully autonomous and intrinsically motivated robot usable for HRI experiments. We argue that an intrinsically motivated approach based on the Predictive Information formalism, like the one presented here, could provide us with a pathway towards autonomous robot behaviour generation, that is capable of producing behaviour interesting enough for sustaining the interaction with humans and without the need for a human operator in the loop. We present a possible reactive baseline behaviour for comparison for future research. Participants perceive the baseline and the adaptive, intrinsically motivated behaviour differently. In our exploratory study we see evidence that participants perceive an intrinsically motivated robot as less intelligent than the reactive baseline behaviour. We argue that is mostly due to the high adaptation rate chosen and the design of the environment. However, we also see that the adaptive robot is perceived as more warm, a factor which carries more weight in interpersonal interaction than competence.


Robotics Sustained interaction Human-robot interaction Autonomous human-robot interaction Robot behaviour Cognitive robotics Robot control Autonomous robots Intrinsic motivation Predictive information Information theory 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of HertfordshireHertfordshireUK
  2. 2.University of WaterlooWaterlooCanada

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