Abstract
During face to face interactions, the emotional state of each participant is greatly affected by the behavior of other participants and how much this behavior conforms with common protocols of interaction in the society. Research in human to human interaction in face to face situations has uncovered many forms of synchrony in the behavior of the interacting partners. This includes factors as body alignment, entrainment of verbal behavior. Maintenance of these kinds of synchrony is essential to keep the interaction natural and to regulate the affective state of the interacting partners.
In this chapter we examine the interplay between one partner’s use of interaction protocols, maintenance of synchrony and the emotional response of the other partner in the two way interactions.
We will first define the notion of interaction protocol and relate it with the Reactive Theory of Intention and Low Level Emotions. We will then show empirically that the use of suitable interaction protocols is essential to maintain a positive emotional response of the interaction partner during face to face explanation situations. The analysis in this section is based on the H 3 R ? interaction corpus containing sixty six human-human and human-robot interaction sessions. This interaction corpus utilizes physiological, behavioral and subjective data.
Using this result, it is necessary to model not only the affective state of the interacting partners but also the interaction protocol that each of them is using. Human-Robot interaction experiments can be of value in analyzing the interaction protocols used by the partners and modelling their emotional response to these protocols.
We used Human-Robot interactions in explanation and collaborative navigation tasks as a test-bed for our analysis of interaction protocol emergence and adaptation.
The first experiment analyzes how the requirement to maintain the interaction protocol and synchrony restricts the design of the robot and how did we meet these restriction in a semi-autonomous miniature robot. We focus on how low level emotions can be used to act as a mediator between Perception and Behavior.
The second experiment explores a computational model of the interaction protocol and evaluates it in an explanation face to face scenario.
The chapter also provides a critical analysis of the interplay between interaction protocols and the emotional state of interaction partners.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mohammad, Y., Xu, Y., Matsumura, K., Nishida, T.: The h 3 r explanation corpus:human-human and base human-robot interaction dataset. In: The fourth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2008), December 2008, pp. 201–206 (2008)
Russell, S.J., Norvig, P.: Artificial intelligence: A modern approach. Prentice-Hall, Englewood (2003)
Searle, J.: Minds, brains and programs. Behavioral and Brain Sciences 3(3) (1980)
Yang, L., Yue, J., Zhang, X.: Hybrid control architecture in bio-mimetic robot, June 2008, pp. 5699–5703 (2008)
Ulam, P., Arkin, R.: Biasing behavioral activation with intent for an entertainment robot. Intelligent Service Robotics 1(3), 195–209 (2008)
Griffiths, P.: Is emotion a natural kind? In: Thinking about feeling, pp. 233–249. Oxford University Press, Oxford (2004)
Barrett, F.L.: Are emotions natural kinds? Perspectives on Psychological Science 1, 28–58 (2006)
Schachter, S., Singer, J.: Cognitive, social, and physiological determinants of emotional state. Psychological Review (69), 379–399 (1962)
Scherer, K.R.: Appraisal Considered as a Process of Multilevel Sequential Checking. In: Appraisal Processes in Emotion: Theory, Methods, Research, pp. 92–120. Oxford University Press, Oxford (2001)
Posner, J., Russell, J.A., Peterson, B.S.: The circumplex model of affect: an integrative approach to affective neuroscience, cognitive development, and psychopathology. Development and psychopathology (3), 715–734 (2005)
Scholsberg, H.: Three dimensions of emotions. Psychological Review (61), 81–88 (1954)
Fontaine, J.R., Scherer, K.R., Roesch, E.B., Ellsworth, P.C.: The world of emotions is not two-dimensional. Psychological Science 18(12), 1050–1057 (2007)
Mandryk, R.L., Inkpen, K.M.: Physiological indicators for the evaluation of co-located collaborative play. In: CSCW 2004: Proceedings of the 2004 ACM conference on Computer supported cooperative work, New York, NY, USA, pp. 102–111. ACM, New York (2004)
Shi, Y., Choi, E.H.C., Ruiz, N., Chen, F., Taib, R.: Galvanic skin respons (gsr) as an index of cognitive load. In: CHI 2007, April 2007, pp. 2651–2656 (2007)
Lang, P.J.: The emotion probe: Studies of motivation and attention. American Psychologiest 50(5), 285–372 (1995)
Lin, T., Hu, W., Omata, M., Imamiya, A.: Do physiological data relate to traditional usability indexes? In: OZCHI 2005 (November 2005)
Mower, E., Feil-Seifer, D.J., Mataric, M.J., Narayanan, S.: Investigating implicit cues for user state estimation in human-robot interaction using physiological measurements. In: 16th International Conference on Robot & Human Interactive Communication, August 2007, pp. 1125–1130 (2007)
Papillo, J.F., Shapiro, D.: The Cardiovascular System. In: Principles of Psychophysiology: Physical, Social, and Inferential Elements. Cambridge University Press, Cambridge (1990)
Rowe, D.W., Sibert, J., Irwin, D.: Heart rate variability: Indicator of user stateas an aid to human-computer interaction. In: Conference on Human Factors in Computing Systems, CHI 1998 (1998)
Breazeal, C.: Affective interaction between humans and robots. In: Kelemen, J., Sosík, P. (eds.) ECAL 2001. LNCS (LNAI), vol. 2159, pp. 582–591. Springer, Heidelberg (2001)
Toda, M.: Design of a fungus-eater. Behavioral Science 7, 164–183 (1962)
Bechara, A.: The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage. Brain and Cognition 55(1), 30–40 (2004)
Mohammad, Y., Nishida, T.: Human adaptation to a miniature robot: Precursors of mutual adaptation. In: The 17th IEEE International Symposium on Robot and Human Interactive Communication, 2008. RO-MAN 2008, pp. 124–129 (2008)
EPFL: http://www.e-puck.org
Mohammad, Y.F.O., Nishida, T.: A new, hri inspired, view of intention. In: AAAI 2007 Workshop on Human Implications of Human-Robot Interactions, July 2007, pp. 21–27 (2007)
Argyle, M.: Bodily Communication, New Ed edition Routledge (2001)
Atienza, R., Zelinsky, E.: Intuitive human-robot interaction through active 3d gaze tracking. In: 11th Int. Symposium of Robotics Research (2003)
Kuno, Y., Sakurai, A., Miyauchi, D., Nakamura, A.: Two-way eye contact between humans and robots. In: ICMI 2004: Proceedings of the 6th international conference on Multimodal interfaces, New York, NY, USA, pp. 1–8. ACM, New York (2004)
Seemann, E., Nickel, K., Stiefelhagen, R.: Head pose estimation using stereo vision for human-robot interaction. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004, pp. 626–631 (2004)
Sidner, C.L., Kidd, C.D., Lee, C., Lesh, N.: Where to look: a study of human-robot engagement. In: IUI 2004: Proceedings of the 9th international conference on Intelligent user interfaces, New York, NY, USA, pp. 78–84. ACM, New York (2004)
Hoffman, M.W., Grimes, D.B., Shon, A.P., Rao, R.P.N.: A probabilistic model of gaze imitation and shared attention. Neural Netw. 19(3), 299–310 (2006)
Gusfield, D.: Algorithms on strings, trees, and sequences: computer science and computational biology. Cambridge University Press, Cambridge (1997)
Sabbagh, M.A.: Understanding orbitofrontal contributions to theory-of-mind reasoning: Implications for autism. Brain and Cognition (55), 209–219 (2004)
Murata, A., et al.: Object representation in the ventral premotor cortex (area f5) of the monkey. Journal of Neurophysiology 78, 2226–2230 (1997)
Oberman, L., et al.: Eeg evidence for mirror neuron activity during the observation of human and robot actions: Toward and analysis of the human qualities of interactive robots. Neurocomputing 70, 2194–2203 (2007)
Mohammad, Y., Nishida, T.: Toward combining autonomy and interactivity for social robots. AI & Society 24(1), 35–49
Kendon, A.: Movement coordination in social interaction: Some examples considered. Acta Pyschologica 32, 1–25 (1970)
Mohammad, Y., Nishida, T.: Constrained motif discovery. In: International Workshop on Data Mining and Statistical Science (DMSS 2008), September 2008, pp. 16–19 (2008)
Mohammad, Y., Nishida, T.: Toward agents that can learn nonverbal interactive behavior. In: IAPR Workshop on Cognitive Information Processing, pp. 164–169 (2008)
Mohammad, Y.F.O., Nishida, T.: A cross-platform robotic architecture for autonomous interactive robots. In: Nguyen, N.T., Borzemski, L., Grzech, A., Ali, M. (eds.) IEA/AIE 2008. LNCS (LNAI), vol. 5027, pp. 108–117. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Mohammad, Y., Nishida, T. (2010). Modelling Interaction Dynamics during Face-to-Face Interactions. In: Nishida, T., Jain, L.C., Faucher, C. (eds) Modeling Machine Emotions for Realizing Intelligence. Smart Innovation, Systems and Technologies, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12604-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-12604-8_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12603-1
Online ISBN: 978-3-642-12604-8
eBook Packages: EngineeringEngineering (R0)