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Understandable Robots: What, Why, and How
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
2018 (Engelska)Ingår i: Paladyn - Journal of Behavioral Robotics, ISSN 2080-9778, E-ISSN 2081-4836, Vol. 9, nr 1, s. 110-123Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

As robots become more and more capable and autonomous, there is an increasing need for humans to understand what the robots do and think. In this paper, we investigate what such understanding means and in- cludes, and how robots can be designed to support un- derstanding. After an in-depth survey of related earlier work, we discuss examples showing that understanding includes not only the intentions of the robot, but also de- sires, knowledge, beliefs, emotions, perceptions, capabil- ities, and limitations of the robot. The term understandingis formally defined, and the term communicative actions is defined to denote the various ways in which a robot may support a human’s understanding of the robot. A novel model of interaction for understanding is presented. The model describes how both human and robot may utilize a first or higher-order theory of mind to understand each other and perform communicative actions in order to sup- port the other’s understanding. It also describes simpler cases in which the robot performs static communicative actions in order to support the human’s understanding of the robot. In general, communicative actions performed by the robot aim at reducing the mismatch between the mind of the robot, and the robot’s inferred model of the human’s model of the mind of the robot. Based on the pro- posed model, a set of questions are formulated, to serve as support when developing and implementing the model in real interacting robots.

Ort, förlag, år, upplaga, sidor
Warsaw, Poland: De Gruyter Open, 2018. Vol. 9, nr 1, s. 110-123
Nyckelord [en]
human-robot interaction, communication, predictable, explainable
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:umu:diva-150156DOI: 10.1515/pjbr-2018-0009Scopus ID: 2-s2.0-85050650946OAI: oai:DiVA.org:umu-150156DiVA, id: diva2:1232841
Tillgänglig från: 2018-07-12 Skapad: 2018-07-12 Senast uppdaterad: 2018-10-26Bibliografiskt granskad

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Hellström, ThomasBensch, Suna

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