A challenge in using robots in human-robot interaction (HRI) is to design behavior that is engaging enough to encourage voluntary, long-term interaction, yet robust to the perturbations induced by human interaction. 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 . We conducted a within-subjects  study (N=24) where participants interacted with a fully autonomous Sphero BB8 robot with different behavioral regimes: one realizing an adaptive, intrinsically motivated behavior and the other being reactive, but not adaptive. A quantitative analysis of post-interaction questionnaires showed a significantly higher perception of the dimension "Warmth" compared to the  baseline behavior. Warmth is considered a primary dimension for social attitude formation in human social cognition. A human perceived as warm (friendly, trustworthy) experiences more positive social interactions . If future work demonstrates that this transfers to human-robot social cognition, then the generic methods presented here could be used to imbue robots with behavior leading to positive perception by and to positive social interaction with humans .
A challenge in using robots in human-inhabited environments is to design behavior that is engaging , yet robust to the perturbations induced by human interaction. 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 . We conducted a within-subjects user study (N=24) where participants interacted with a fully autonomous Sphero BB8 robot with different behavioral regimes: one realizing an adaptive, intrinsically motivated behavior and the other being reactive, but not adaptive. A quantitative analysis of post-interaction questionnaires showed a significantly higher perception of the dimension "Warmth" compared to the reactive baseline behavior. Warmth is considered a primary dimension for social attitude formation in human social cognition. A human perceived as warm (friendly, trustworthy) experiences more positive social interactions .
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human-robot interaction (HRI)
human-inhabited environments
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enough to encourage voluntary, long-term interaction,
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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
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
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user
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reactive
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. If future work demonstrates that this transfers to human-robot social cognition, then the generic methods presented here could be used to imbue robots with behavior leading to positive perception by and to positive social interaction with humans