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Robots in the Wild

Robots in the Wild. Dirk Heylen Human Media Interaction University of Twente. SERA. Social Engagement with Robots and Agents FP7 2009-2010 Partners OFAI: Sabine Payr, Paolo Petta Duisburg: Nicole Krämer Sheffield: Peter Wallis University of Twente: Dirk Heylen. Goal/Questions.

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Robots in the Wild

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  1. Robots in the Wild Dirk Heylen Human Media Interaction University of Twente

  2. SERA • Social Engagement with Robots and Agents • FP7 • 2009-2010 • Partners • OFAI: Sabine Payr, Paolo Petta • Duisburg: Nicole Krämer • Sheffield: Peter Wallis • University of Twente: Dirk Heylen

  3. Goal/Questions • What makes social agents/robots social? • How do people interact with “social” a/r? • How can we design/implement social a/r?

  4. Robot set-up: elements • Nabaztag • Passive infrared sensor • Key hook switch • Dialogue system • RFID cards • Activity Plan • System Clock

  5. What did we do? • Put robot set-up in people’s home for 10 days. • Videotaped interactions • Complemented with interviews and logbooks • Analysed data • Three iterations: expanding repertoire

  6. Diagram

  7. Scenario • Older people (50+) • Promote healthy life-style • Transtheoretical model of behaviour change • Precontemplation • Contemplation • Preparation • Action • Maintenance

  8. Actions • In general • planning • goal setting • self-reflection • self-monitoring • self-confidence • Exercise monitor and self-reflection plan from the British Heart Foundation

  9. Video

  10. Kinds of dialogue • First appearance of the participant in the morning • Participant goes out • Participant returns home • After last activity of the day • Message • Message retrieval

  11. Acceptance / Use • First iteration: • not very useful • easy to use • continue to use • technical difficulties • limitations in dialogue • fun to use

  12. What does it mean to be social? • To have a Theory of Mind? • To show “social” behaviours? • To be able to sense and express affect? • To be competent in interpersonal skills? • To be able to communicate? • To what degree is is necessary to model all this?

  13. Compare • Karin • INES • Angelica

  14. Comparing Architecture • On a high level, the various systems have a very similar architecture. • The similarity derives from the common functionality of the systems to mimic human interactive skills.

  15. Architecture • In one way, one could say that the main differences across the architectures of the systems relate to a few components which are absent or less articulated in some systems and more involved in others. • In particular, these are concerned with “affect sensing”, “user modelling”, (i.e. consideration for immaterial aspects of the scenarios) and the complexity of the virtual mind of the agent/robot (i.e., how complex a character it is).

  16. on modelling • In another way, one could say that there is an underlying dimension along which implementations of social systems differ. • On the one hand there are systems that are committed to model particular human cognitive functions that are seen to be involved in human social behaviour (the cognitive approach) and • on the other there are those that try to get the system to display social behaviours without such regard for cognitive modelling (the “behaviourist" approach, one could say).

  17. On modelling • Accounting for the social dimensions of the interaction is not necessarily expressed in architectural, i.e. structural, differences only, • but also in the content that is implemented (the range of behaviours that can be displayed, the kinds of dialogue acts that can be performed, the range of emotions that can be sensed and expressed).

  18. So • Modelling or pretending? • Stance taking • the eye of the beholder • HCI: the mental model • switching between machine + social actor • switching between involved in the task, involved in the experiment, involved in reflection

  19. Finally • Some tools: • DiaGraphEditor and Visualisation • FLIPPER = variant of DIPPER • information state • preconditions / update rules

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