Before revision:  Here we evaluate if a physical robot that generates its behavior based on its intrinsic motivations could address this challenge. We use an information theoretic quantity - predictive information maximization - as an intrinsic motivation, as simulated experiments showed that this leads to playful, exploratory behavior that is robust to changes to the robot 's morphology and to its environment. We present a game-like study design, which allows us to focus on the interplay between the robot and the human participant. In contrast to a study design where participants order or control a robot to do a specific task, the robot andthe human participants in our study design explore their behaviors without any specific goals .
After revision:  Our idea is to imbue the robot with intrinsic motivation (IM) so that it can handle new situations and appears as a genuine social other to humans and thus be of more interest to a human interaction partner. Human-robot interaction (HRI) experiments mainly focus on scripted or teleoperated robots, that mimic characteristics such as IM to control isolated behavior factors. This article presents a "robotologist" study design that allows comparing autonomously generated behaviors with each other, and, for the first time, evaluates the human perception of IM-based generated behavior in robots .