10:00   Oral Session 1-KZ – Robots & Artificial Agents 1
Chair: Jonathan Gratch
25 mins
Empathizing with Robots: Fellow Feeling along the Anthropomorphic Spectrum
Laurel D. Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, Peter Robinson
Abstract: A long-standing question within the robotics community is about the degree of human-likeness robots ought to have when interacting with humans. We explore an unexamined aspect of this problem: how people empathize with robots along the anthropomorphic spectrum. We conducted a web-based experiment (n = 120) that measured how people empathized with four different robots shown to be experiencing mistreatment by humans. Our results indicate that people empathize more strongly with more human-looking robots and less with mechanical looking robots. We also found that a person’s general ability to empathize has no predictive value for expressed empathy toward robots.
25 mins
How about laughter? Perceived naturalness of two laughing humanoid robots
Christian Werner Becker-Asano, Takayuki Kanda, Carlos Ishi, Hiroshi Ishiguro
Abstract: As humanoid robots will have to behave socially adequate in a future society, we started to investigate laughter as an important para-verbal signal influencing relationships among humans quite easily. As a first step we investigate, how humanoid robots might laugh within a situation, which is suitable for laughter. Given the variety of human laughter, do people prefer a certain style for a robot’s laughter? And if yes, how does a robot’s outer appearance affect this preference, if at all? Accordingly, we combined six recordings of female laughter with body movements for two different humanoid robots with the aim to evaluate their perceived naturalness using two types of video-based surveys. We not only found that people indeed prefer one type of laughter when being forced to choose, but the results also suggest significant differences in the perceived naturalness of laughter with regard to the participant’s cultural background. The outer appearance seems to change the perceived naturalness of a humanoid robot’s laughter only on a global level. It is evident, however, that further research on this rather unexplored topic is needed as much as it promises to provide valuable means to support the development of social robots.
25 mins
"Don't think too much!" - Artificial Somatic Markers for Action Selection
César F. Pimentel, Maria R. Cravo
Abstract: Humans could not effectively perform everyday decisions if they could only count on purely rational evaluations of the available response options. According to the Somatic Marker hypothesis, before such evaluations take place, emotional signals drastically reduce the space of available options and provide essential biases for decision making. Within the context of action selection, we present a model of the somatic markers' mechanism, encompassing three related processes of an AI agent: 1) Creating markers from the agent's experiences; 2) Combining markers and producing generalizations; 3) Using existing markers to aid in action selection. Computer simulations in two different domains respectively show: a) a resulting behavior that is similar to that obtained from an experiment with human subjects, and b) an intuitive creation and effect of generalized markers.