Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Paladyn, Journal of Behavioral Robotics

Editor-in-Chief: Schöner, Gregor

1 Issue per year

Open Access
Online
ISSN
2081-4836
See all formats and pricing
More options …

Towards the synthetic self: making others perceive me as an other

Stephane Lallee
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain; Institute for Infocomm Research, A*STAR, Singapore
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Vasiliki Vouloutsi
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Maria Blancas Munoz
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Klaudia Grechuta
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jordi-Ysard Puigbo Llobet
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Marina Sarda
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Paul F.M.J. Verschure
  • Synthetic Perceptive Emotive Cognitive Systems group, Universitat Pompeu Fabra, Barcelona, Spain
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-07-20 | DOI: https://doi.org/10.1515/pjbr-2015-0010

Abstract

Future applications of robotic technologies will involve interactions with non-expert humans as machines will assume the role of companions, teachers or healthcare assistants. In all those tasks social behavior is a key ability that needs to be systematically investigated and modelled at the lowest level, as even a minor inconsistency of the robot’s behavior can greatly affect the way humans will perceive it and react to it. Here we propose an integrated architecture for generating a socially competent robot.We validate our architecture using a humanoid robot, demonstrating that gaze, eye contact and utilitarian emotions play an essential role in the psychological validity or social salience of Human-Robot Interaction (HRI). We show that this social salience affects both the empathic bonding between the human and a humanoid robot and, to a certain extent, the attribution of a Theory of Mind (ToM). More specifically, we investigate whether these social cues affect other utilitarian aspects of the interaction such as knowledge transfer within a teaching context.

Keywords : Human-Robot Interaction; Social Robotics; Attention and Emotion; Cognitive Architecture; Behavioral Compositionality

References

  • [1] Y. Fernaeus, M. Håkansson, M. Jacobsson, and S. Ljungblad, “How do you play with a robotic toy animal?: a long-term study of pleo,” in Proceedings of the 9th international Conference on interaction Design and Children, pp. 39–48, ACM, 2010. Google Scholar

  • [2] M. Saerbeck, T. Schut, C. Bartneck, and M. D. Janse, “Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1613–1622, ACM, 2010. Google Scholar

  • [3] K.Wada and T. Shibata, “Robot therapy in a care house-results of case studies,” in Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium on, pp. 581–586, IEEE, 2006. Google Scholar

  • [4] J. Sung, H. I. Christensen, and R. E. Grinter, “Robots in the wild: understanding long-term use,” in Human-Robot Interaction (HRI), 2009 4th ACM/IEEE International Conference on, pp. 45–52, IEEE, 2009. Google Scholar

  • [5] M. Trincavelli, M. Reggente, S. Coradeschi, A. Loutfi, H. Ishida, and A. J. Lilienthal, “Towards environmental monitoring with mobile robots,” in Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, pp. 2210–2215, IEEE, 2008. Google Scholar

  • [6] K. Dautenhahn, S. Woods, C. Kaouri, M. L. Walters, K. L. Koay, and I. Werry, “What is a robot companion-friend, assistant or butler?,” in Intelligent Robots and Systems, 2005.(IROS 2005). 2005 IEEE/RSJ International Conference on, pp. 1192–1197, IEEE, 2005. Google Scholar

  • [7] S. Thrun, M. Montemerlo, H. Dahlkamp, D. Stavens, A. Aron, J. Diebel, P. Fong, J. Gale, M. Halpenny, G. Hoffmann, et al., “Stanley: The robot that won the darpa grand challenge,” Journal of field Robotics, vol. 23, no. 9, pp. 661–692, 2006. Google Scholar

  • [8] J. Markoff, “Google cars drive themselves, in traflc,” The New York Times, vol. 10, p. A1, 2010. Google Scholar

  • [9] E. Guizzo, “How google?s self-driving car works,” IEEE Spectrum Online, October, vol. 18, 2011. Google Scholar

  • [10] D. Sakamoto, T. Kanda, T. Ono, H. Ishiguro, and N. Hagita, “Android as a telecommunication mediumwith a human-like presence,” in Human-Robot Interaction (HRI), 2007 2nd ACM/IEEE International Conference on, pp. 193–200, IEEE, 2007. Google Scholar

  • [11] P. F. Verschure, “Distributed adaptive control: A theory of the mind, brain, body nexus,” Biologically Inspired Cognitive Architectures, 2012. Google Scholar

  • [12] T. Fong, I. Nourbakhsh, and K. Dautenhahn, “A survey of socially interactive robots,” Robotics and autonomous systems, vol. 42, no. 3, pp. 143–166, 2003. Google Scholar

  • [13] M. A. Goodrich and A. C. Schultz, “Human-robot interaction: a survey,” Foundations and trends in human-computer interaction, vol. 1, no. 3, pp. 203–275, 2007. Google Scholar

  • [14] C. Breazeal, “Toward sociable robots,” Robotics and Autonomous Systems, vol. 42, no. 3, pp. 167–175, 2003. Google Scholar

  • [15] I. Leite, C.Martinho, and A. Paiva, “Social robots for long-term interaction: a survey,” International Journal of Social Robotics, vol. 5, no. 2, pp. 291–308, 2013. Google Scholar

  • [16] S. Thrun, “Toward a framework for human-robot interaction,” Human–Computer Interaction, vol. 19, no. 1-2, pp. 9–24, 2004. Google Scholar

  • [17] C. D. Kidd and C. Breazeal, “Robots at home: Understanding long-term human-robot interaction,” in Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, pp. 3230–3235, IEEE, 2008. Google Scholar

  • [18] K. Wada and T. Shibata, “Living with seal robots in a care house-evaluations of social and physiological influences,” in Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on, pp. 4940–4945, IEEE, 2006. Google Scholar

  • [19] T. Kanda, H. Ishiguro, M. Imai, and T. Ono, “Development and evaluation of interactive humanoid robots,” Proceedings of the IEEE, vol. 92, no. 11, pp. 1839–1850, 2004. Google Scholar

  • [20] A. M. Sabelli, T. Kanda, and N. Hagita, “A conversational robot in an elderly care center: an ethnographic study,” in Human- Robot Interaction (HRI), 2011 6th ACM/IEEE International Conference on, pp. 37–44, IEEE, 2011. Google Scholar

  • [21] C. Breazeal and B. Scassellati, “A context-dependent attention system for a social robot,” in Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pp. 1146–1153, Morgan Kaufmann Publishers Inc., 1999. Google Scholar

  • [22] Y. Bar-Cohen and C. Breazeal, “Biologically inspired intelligent robots,” in Smart Structures andMaterials, pp. 14–20, International Society for Optics and Photonics, 2003. Google Scholar

  • [23] P.-Y. Oudeyer, F. Kaplan, and V. V. Hafner, “Intrinsic motivation systems for autonomous mental development,” Evolutionary Computation, IEEE Transactions on, vol. 11, no. 2, pp. 265–286, 2007. Google Scholar

  • [24] M. Asada, K. Hosoda, Y. Kuniyoshi, H. Ishiguro, T. Inui, Y. Yoshikawa, M. Ogino, and C. Yoshida, “Cognitive developmental robotics: a survey,” Autonomous Mental Development, IEEE Transactions on, vol. 1, no. 1, pp. 12–34, 2009. Google Scholar

  • [25] R. P. Rao, A. P. Shon, and A. N. Meltzoff, “A bayesian model of imitation in infants and robots,” Imitation and social learning in robots, humans, and animals, pp. 217–247, 2004. Google Scholar

  • [26] C. Breazeal and B. Scassellati, “Robots that imitate humans,” Trends in cognitive sciences, vol. 6, no. 11, pp. 481–487, 2002. Google Scholar

  • [27] G. Butterworth and N. Jarrett, “What minds have in common is space: Spatial mechanisms serving joint visual attention in infancy,” British journal of developmental psychology, vol. 9, no. 1, pp. 55–72, 1991. Google Scholar

  • [28] C. Moore and P. Dunham, Joint attention: Its origins and role in development. Psychology Press, 2014. Google Scholar

  • [29] G. J. DuPaul, K. E. McGoey, T. L. Eckert, and J. VanBrakle, “Preschool children with attention-deficit/hyperactivity disorder: impairments in behavioral, social, and school functioning,” Journal of the American Academy of Child & Adolescent Psychiatry, vol. 40, no. 5, pp. 508–515, 2001. CrossrefGoogle Scholar

  • [30] S. Milgram, “Behavioral study of obedience.,” The Journal of Abnormal and Social Psychology, vol. 67, no. 4, p. 371, 1963. Google Scholar

  • [31] S. Milgram and E. Van den Haag, “Obedience to authority,” 1978. Google Scholar

  • [32] B. Reeves and C. Nass, How people treat computers, television, and new media like real people and places. CSLI Publications and Cambridge university press, 1996. Google Scholar

  • [33] Y. Fernaeus, S. Ljungblad, M. Jacobsson, and A. Taylor, “Where third wave hci meets hri: report from a workshop on usercentred design of robots,” in Human-Robot Interaction (HRI), 2009 4th ACM/IEEE International Conference on, pp. 293–294, IEEE, 2009. Google Scholar

  • [34] K. Dautenhahn, “Socially intelligent robots: dimensions of human–robot interaction,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 362, no. 1480, pp. 679–704, 2007. Google Scholar

  • [35] A. Michotte, “The perception of causality.,” 1963. Google Scholar

  • [36] S. Gallagher, How the body shapes the mind. Cambridge Univ Press, 2005. Google Scholar

  • [37] F. Heider, “Social perception and phenomenal causality.,” Psychological review, vol. 51, no. 6, p. 358, 1944. Google Scholar

  • [38] B. J. Scholl, “Objects and attention: The state of the art,” Cognition, vol. 80, no. 1, pp. 1–46, 2001. Google Scholar

  • [39] D. Premack and A. J. Premack, “Origins of human social competence.,” 1995. Google Scholar

  • [40] C. Breazeal, “Emotion and sociable humanoid robots,” International Journal of Human-Computer Studies, vol. 59, no. 1, pp. 119–155, 2003. Google Scholar

  • [41] K. Eng, R. J. Douglas, and P. F. Verschure, “An interactive space that learns to influence human behavior,” Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 35, no. 1, pp. 66–77, 2005. Google Scholar

  • [42] V. Gallese and T. Metzinger, “Motor ontology: the representational reality of goals, actions and selves,” Philosophical Psychology, vol. 16, no. 3, pp. 365–388, 2003. CrossrefGoogle Scholar

  • [43] H. L. Gallagher and C. D. Frith, “Functional imaging of ?theory of mind?,” Trends in cognitive sciences, vol. 7, no. 2, pp. 77–83, 2003. Google Scholar

  • [44] M. Inderbitzin, A. Valjamae, J. M. B. Calvo, P. F. Verschure, and U. Bernardet, “Expression of emotional states during locomotion based on canonical parameters,” in Automatic Face&Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on, pp. 809–814, IEEE, 2011. Google Scholar

  • [45] P. Ekman, “An argument for basic emotions,” Cognition&Emotion, vol. 6, no. 3-4, pp. 169–200, 1992. Google Scholar

  • [46] J.-D. Boucher, U. Pattacini, A. Lelong, G. Bailly, F. Elisei, S. Fagel, P. F. Dominey, and J. Ventre-Dominey, “I reach faster when i see you look: gaze effects in human–human and human–robot face-to-face cooperation,” Frontiers in neurorobotics, vol. 6, 2012. Google Scholar

  • [47] A. Frischen, A. P. Bayliss, and S. P. Tipper, “Gaze cueing of attention: visual attention, social cognition, and individual differences.,” Psychological bulletin, vol. 133, no. 4, p. 694, 2007. CrossrefGoogle Scholar

  • [48] S. Lallée, K.Hamann, J. Steinwender, F.Warneken, U.Martienz, H. Barron-Gonzales, U. Pattacini, I. Gori, M. Petit, G. Metta, et al., “Cooperative human robot interaction systems: Iv. communication of shared plans with naïve humans using gaze and speech,” in Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on, pp. 129–136, IEEE, 2013. Google Scholar

  • [49] M. Knapp, J. Hall, and T. Horgan, Nonverbal communication in human interaction. Cengage Learning, 2013. Google Scholar

  • [50] M. Argyle and J. Dean, “Eye-contact, distance and aflliation,” Sociometry, pp. 289–304, 1965. Google Scholar

  • [51] B.Mutlu, J. Forlizzi, and J. Hodgins, “A storytelling robot: Modeling and evaluation of human-like gaze behavior,” in Humanoid Robots, 2006 6th IEEE-RAS International Conference on, pp. 518–523, IEEE, 2006. Google Scholar

  • [52] C. Brown, “Gaze controls with interactions and decays,” Systems, Man and Cybernetics, IEEE Transactions on, vol. 20, no. 2, pp. 518–527, 1990. Google Scholar

  • [53] T. Ono, M. Imai, and R. Nakatsu, “Reading a robot’s mind: a model of utterance understanding based on the theory of mind mechanism,” Advanced Robotics, vol. 14, no. 4, pp. 311–326, 2000. Google Scholar

  • [54] C. Breazeal, C. D. Kidd, A. L. Thomaz, G. Hoffman, and M. Berlin, “Effects of nonverbal communication on eflciency and robustness in human-robot teamwork,” in Intelligent Robots and Systems, 2005.(IROS 2005). 2005 IEEE/RSJ International Conference on, pp. 708–713, IEEE, 2005. Google Scholar

  • [55] P. F. Verschure, B. J. Kröse, and R. Pfeifer, “Distributed adaptive control: The self-organization of structured behavior,” Robotics and Autonomous Systems, vol. 9, no. 3, pp. 181–196, 1992. Google Scholar

  • [56] M. S. Fibla, U. Bernardet, and P. F. Verschure, “Allostatic control for robot behaviour regulation: An extension to path planning,” in Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pp. 1935–1942, IEEE, 2010. Google Scholar

  • [57] M. Sanchez-Fibla, U. Bernardet, E. Wasserman, T. Pelc, M. Mintz, J. C. Jackson, C. Lansink, C. Pennartz, and P. F. Verschure, “Allostatic control for robot behavior regulation: a comparative rodent-robot study,” Advances in Complex Systems, vol. 13, no. 03, pp. 377–403, 2010. Google Scholar

  • [58] P. F. Verschure, “Formal minds and biological brains ii: from the mirage of intelligence to a science and engineering of consciousness,” 2013. Google Scholar

  • [59] T. J. Prescott, N. Lepora, and P. F. Vershure, “A future of living machines?: International trends and prospects in biomimetic and biohybrid systems,” in SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring, pp. 905502–905502, International Society for Optics and Photonics, 2014. Google Scholar

  • [60] P. F. Verschure, “Real-world behavior as a constraint on the cognitive architecture: Comparing act-r and dac in the newell test,” Behavioral and Brain Sciences, vol. 26, no. 05, pp. 624– 626, 2003. Google Scholar

  • [61] J. R. Anderson, M. Matessa, and C. Lebiere, “Act-r: A theory of higher level cognition and its relation to visual attention,” Human-Computer Interaction, vol. 12, no. 4, pp. 439– 462, 1997. Google Scholar

  • [62] J. R. Anderson, How can the human mind occur in the physical universe? Oxford University Press, 2007. Google Scholar

  • [63] J. Laird, The Soar cognitive architecture. MIT Press, 2012. Google Scholar

  • [64] P. F. Verschure, C. M. Pennartz, and G. Pezzulo, “The why, what, where, when and how of goal-directed choice: neuronal and computational principles,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 369, no. 1655, p. 20130483, 2014. Google Scholar

  • [65] P. F. Verschure and R. Pfeifer, “Environment interaction: a case study in autonomous systems,” in From Animals to Animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior, vol. 2, p. 210, MIT Press, 1993. Google Scholar

  • [66] S. Lallee, C. Madden, M. Hoen, and P. F. Dominey, “Linking language with embodied and teleological representations of action for humanoid cognition,” Frontiers in neurorobotics, vol. 4, 2010. Google Scholar

  • [67] R.Matthews, N. J. McDonald, P. Hervieux, P. J. Turner, and M. A. Steindorf, “A wearable physiological sensor suite for unobtrusive monitoring of physiological and cognitive state,” in Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp. 5276– 5281, IEEE, 2007. Google Scholar

  • [68] S. Badia, A. Valjamae, F. Manzi, U. Bernardet, A. Mura, J. Manzolli, and P. Verschure, “The effects of explicit and implicit interaction on user experiences in a mixed reality installation: The synthetic oracle,” Presence, vol. 18, no. 4, pp. 277–285, 2009. Google Scholar

  • [69] D. J. Cook and S. K. Das, “How smart are our environments? an updated look at the state of the art,” Pervasive and mobile computing, vol. 3, no. 2, pp. 53–73, 2007. Google Scholar

  • [70] K. Eng, D. Klein, A. Babler, U. Bernardet, M. Blanchard, M. Costa, T. Delbrück, R. J. Douglas, K. Hepp, J.Manzolli, et al., “Design for a brain revisited: the neuromorphic design and functionality of the interactive space ‘Ada’,” Reviews in the Neurosciences, vol. 14, no. 1-2, pp. 145–180, 2003. Google Scholar

  • [71] M. Tenorth, A. C. Perzylo, R. Lafrenz, and M. Beetz, “The roboearth language: Representing and exchanging knowledge about actions, objects, and environments,” in Robotics and Automation (ICRA), 2012 IEEE International Conference on, pp. 1284–1289, IEEE, 2012. Google Scholar

  • [72] S. Lallée, U. Pattacini, J.-D. Boucher, S. Lemaignan, A. Lenz, C. Melhuish, L. Natale, S. Skachek, K. Hamann, J. Steinwender, et al., “Towards a platform-independent cooperative humanrobot interaction system: Ii. perception, execution and imitation of goal directed actions,” in Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pp. 2895–2902, IEEE, 2011. Google Scholar

  • [73] D. Cañamero, “Modeling motivations and emotions as a basis for intelligent behavior,” in Proceedings of the first international conference on Autonomous agents, pp. 148–155, ACM, 1997. Google Scholar

  • [74] C. Hull, “Principles of behavior,” 1943. Google Scholar

  • [75] W. B. Cannon, “The wisdom of the body,” The American Journal of the Medical Sciences, vol. 184, no. 6, p. 864, 1932. Google Scholar

  • [76] J. P. Seward, “Drive, incentive, and reinforcement.,” Psychological review, vol. 63, no. 3, p. 195, 1956. Google Scholar

  • [77] B. S. McEwen and J. C. Wingfield, “The concept of allostasis in biology and biomedicine,” Hormones and behavior, vol. 43, no. 1, pp. 2–15, 2003. Google Scholar

  • [78] D. S. Goldstein and B. McEwen, “Allostasis, homeostats, and the nature of stress,” Stress: The International Journal on the Biology of Stress, vol. 5, no. 1, pp. 55–58, 2002. Google Scholar

  • [79] D. McFarland, “Experimental investigation of motivational state,” Motivational control systems analysis, pp. 251–282, 1974. Google Scholar

  • [80] A. H. Maslow, “A theory of human motivation,” Published in, 1943. Google Scholar

  • [81] M. A. Arbib and J.-M. Fellous, “Emotions: from brain to robot,” Trends in cognitive sciences, vol. 8, no. 12, pp. 554–561, 2004. Google Scholar

  • [82] K. R. Scherer, “Neuroscience projections to current debates in emotion psychology,” Cognition & Emotion, vol. 7, no. 1, pp. 1– 41, 1993. Google Scholar

  • [83] A. Damasio, Descartes’ error: Emotion, reason, and the human brain. Penguin Books, 2005. Google Scholar

  • [84] J.-M. Fellous and J. E. Ledoux, “Toward basic principles for emotional processing: What the fearful brain tells the robot,” Who needs emotions, pp. 79–115, 2005. Google Scholar

  • [85] M. Cabanac, “What is emotion?,” Behavioural processes, vol. 60, no. 2, pp. 69–83, 2002. Google Scholar

  • [86] N. H. Frijda, The emotions. Cambridge University Press, 1986. Google Scholar

  • [87] M. Risler and O. von Stryk, “Formal behavior specification of multi-robot systems using hierarchical state machines in xabsl,” in AAMAS08-workshop on formal models and methods for multi-robot systems, Estoril, Portugal, Citeseer, 2008. Google Scholar

  • [88] P. Verschure, “Connectionist explanation: Taking positions in the mind-brain dilemma,” Neural networks and a new artificial intelligence, pp. 133–188, 1997. Google Scholar

  • [89] G. Metta, L. Natale, F. Nori, G. Sandini, D. Vernon, L. Fadiga, C. Von Hofsten, K. Rosander, M. Lopes, J. Santos-Victor, et al., “The icub humanoid robot: An open-systems platform for research in cognitive development,” Neural Networks, vol. 23, no. 8, pp. 1125–1134, 2010. Google Scholar

  • [90] G. Geiger, N. Alber, S. Jordà, and M. Alonso, “The reactable: A collaborative musical instrument for playing and understanding music,” Her&Mus. Heritage &Museography, no. 4, pp. 36– 43, 2010. Google Scholar

  • [91] H. Cramer, N. Kemper, A. Amin, B.Wielinga, and V. Evers, “?give me a hug?: the effects of touch and autonomy on people’s responses to embodied social agents,” Computer Animation and Virtual Worlds, vol. 20, no. 2-3, pp. 437–445, 2009. Google Scholar

  • [92] H. Cramer, A. Amin, V. Evers, and N. Kemper, “Touched by robots: effects of physical contact and proactiveness,” arXiv. org e-Print archive, no. INS-E0903, pp. 1–11, 2009. Google Scholar

  • [93] M. K. Ackerman and G. S. Chirikjian, “A probabilistic solution to the ax= xb problem: Sensor calibration without correspondence,” in Geometric Science of Information, pp. 693– 701, Springer, 2013. Google Scholar

  • [94] M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, and A. Y. Ng, “Ros: an open-source robot operating system,” in ICRA workshop on open source software, vol. 3, p. 5, 2009. Google Scholar

  • [95] C. L. Colby, “Action-oriented spatial reference frames in cortex,” Neuron, vol. 20, no. 1, pp. 15–24, 1998. Google Scholar

  • [96] G. Vallar, E. Lobel, G. Galati, A. Berthoz, L. Pizzamiglio, and D. Le Bihan, “A fronto-parietal system for computing the egocentric spatial frame of reference in humans,” Experimental Brain Research, vol. 124, no. 3, pp. 281–286, 1999. CrossrefGoogle Scholar

  • [97] Y. E. Cohen and R. A. Andersen, “A common reference frame for movement plans in the posterior parietal cortex,” Nature Reviews Neuroscience, vol. 3, no. 7, pp. 553–562, 2002. Google Scholar

  • [98] R. Chatila and J.-P. Laumond, “Position referencing and consistent world modeling for mobile robots,” in Robotics and Automation. Proceedings. 1985 IEEE International Conference on, vol. 2, pp. 138–145, IEEE, 1985. Google Scholar

  • [99] S. Coradeschi and A. Saflotti, “An introduction to the anchoring problem,” Robotics and Autonomous Systems, vol. 43, no. 2, pp. 85–96, 2003. Google Scholar

  • [100] L. Steels and J.-C. Baillie, “Shared grounding of event descriptions by autonomous robots,” Robotics and autonomous systems, vol. 43, no. 2, pp. 163–173, 2003. Google Scholar

  • [101] J. Fritsch, M. Kleinehagenbrock, S. Lang, T. Plötz, G. A. Fink, and G. Sagerer, “Multi-modal anchoring for human–robot interaction,” Robotics and Autonomous Systems, vol. 43, no. 2, pp. 133–147, 2003. Google Scholar

  • [102] A. Chella, S. Coradeschi, M. Frixione, and A. Saflotti, “Perceptual anchoring via conceptual spaces,” in proceedings of the AAAI-04 workshop on anchoring symbols to sensor data, pp. 40–45, 2004. Google Scholar

  • [103] A. Bonarini, M. Matteucci, and M. Restelli, “Concepts for anchoring in robotics,” in AI* IA 2001: Advances in Artificial Intelligence, pp. 327–332, Springer, 2001. Google Scholar

  • [104] I. H. Suh, G. H. Lim, W. Hwang, H. Suh, J.-H. Choi, and Y.-T. Park, “Ontology-based multi-layered robot knowledge framework (omrkf) for robot intelligence,” in Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, pp. 429–436, IEEE, 2007. Google Scholar

  • [105] S. Lemaignan, R. Ros, L. Mosenlechner, R. Alami, and M. Beetz, “Oro, a knowledge management platform for cognitive architectures in robotics,” in Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pp. 3548–3553, IEEE, 2010. Google Scholar

  • [106] M. Tenorth and M. Beetz, “Knowrob—knowledge processing for autonomous personal robots,” in Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pp. 4261–4266, IEEE, 2009. Google Scholar

  • [107] L. Seabra Lopes and A. Teixeira, “Human-robot interaction through spoken language dialogue,” in Intelligent Robots and Systems, 2000.(IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on, vol. 1, pp. 528–534, IEEE, 2000. Google Scholar

  • [108] D. Spiliotopoulos, I. Androutsopoulos, and C. D. Spyropoulos, “Human-robot interaction based on spoken natural language dialogue,” in Proceedings of the European Workshop on Service and Humanoid Robots, pp. 25–27, 2001. Google Scholar

  • [109] M. Johnson-Roberson, J. Bohg, G. Skantze, J. Gustafson, R. Carlson, B. Rasolzadeh, and D. Kragic, “Enhanced visual scene understanding through human-robot dialog,” in Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pp. 3342–3348, IEEE, 2011. Google Scholar

  • [110] J. Panksepp and L. Biven, “The archaeology of mind,” 2011. Google Scholar

  • [111] C. Breazeal et al., “A motivational system for regulating human-robot interaction,” in AAAI/IAAI, pp. 54–61, 1998. Google Scholar

  • [112] P. Vargas, R. Moioli, L. N. de Castro, J. Timmis, M. Neal, and F. J. Von Zuben, “Artificial homeostatic system: a novel approach,” in Advances in Artificial Life, pp. 754–764, Springer, 2005. Google Scholar

  • [113] R. C. Arkin, M. Fujita, T. Takagi, and R. Hasegawa, “An ethological and emotional basis for human–robot interaction,” Robotics and Autonomous Systems, vol. 42, no. 3, pp. 191–201, 2003. Google Scholar

  • [114] S. Kernbach and O. Kernbach, “Collective energy homeostasis in a large-scale microrobotic swarm,” Robotics and Autonomous Systems, vol. 59, no. 12, pp. 1090–1101, 2011. Google Scholar

  • [115] B. R. Duffy, G. Joue, and J. Bourke, “Issues in assessing performance of social robots,” in Proceedings of the Second WSEAS International Conference, RODLICS, Greece, 2002. Google Scholar

  • [116] K. F.MacDorman and S. J. Cowley, “Long-term relationships as a benchmark for robot personhood,” in Robot and Human Interactive Communication, 2006.ROMAN2006. The 15th IEEE International Symposium on, pp. 378–383, IEEE, 2006. Google Scholar

  • [117] P. H. Kahn, H. Ishiguro, B. Friedman, and T. Kanda, “What is a human?-toward psychological benchmarks in the field of human-robot interaction,” in Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium on, pp. 364–371, IEEE, 2006. Google Scholar

  • [118] S. Lallée, V. Vouloutsi, S. Wierenga, U. Pattacini, and P. Verschure, “EFAA: a companion emerges from integrating a layered cognitive architecture,” in Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, pp. 105–105, ACM, 2014. Google Scholar

  • [119] V. Vouloutsi, K. Grechuta, S. Lallée, and P. F. Verschure, “The influence of behavioral complexity on robot perception,” in Biomimetic and Biohybrid Systems, pp. 332–343, Springer, 2014. Google Scholar

  • [120] C. Bartneck, D. Kulić, E. Croft, and S. Zoghbi, “Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots,” International journal of social robotics, vol. 1, no. 1, pp. 71–81, 2009. Google Scholar

  • [121] V. Vouloutsi, S. Lallée, and P. F. Verschure, “Modulating behaviors using allostatic control,” in Biomimetic and Biohybrid Systems, pp. 287–298, Springer, 2013. Google Scholar

  • [122] T. Koda, “Agents with faces: A study on the effects of personification of software agents. master’s thesis,” 1996. Google Scholar

  • [123] C. Bartneck, M. Verbunt, O. Mubin, and A. Al Mahmud, “To kill a mockingbird robot,” in Human-Robot Interaction (HRI), 2007 2nd ACM/IEEE International Conference on, pp. 81–87, IEEE, 2007. Google Scholar

  • [124] M. S. Gou, V. Vouloutsi, K. Grechuta, S. Lallée, and P. F. Verschure, “Empathy in humanoid robots,” in Biomimetic and Biohybrid Systems, pp. 423–426, Springer, 2014. Google Scholar

  • [125] M. L. Hoffman, Empathy and moral development: Implications for caring and justice. Cambridge University Press, 2001. Google Scholar

  • [126] H. G. Engen and T. Singer, “Empathy circuits,” Current opinion in neurobiology, vol. 23, no. 2, pp. 275–282, 2013. Google Scholar

  • [127] Y. Kim, S. S. Kwak, and M.-s. Kim, “Am i acceptable to you? effect of a robot?s verbal language forms on people?s social distance from robots,” Computers in Human Behavior, vol. 29, no. 3, pp. 1091–1101, 2013. Google Scholar

  • [128] D. Sakamoto, T. Kanda, T. Ono, M. Kamashima, M. Imai, and H. Ishiguro, “Cooperative embodied communication emerged by interactive humanoid robots,” International Journal of Human-Computer Studies, vol. 62, no. 2, pp. 247–265, 2005. Google Scholar

  • [129] S. Milgram, “Some conditions of obedience and disobedience to authority,” Human relations, vol. 18, no. 1, pp. 57–76, 1965. Google Scholar

  • [130] D. Jolliffe and D. P. Farrington, “Development and validation of the basic empathy scale,” Journal of adolescence, vol. 29, no. 4, pp. 589–611, 2006. Google Scholar

  • [131] F. D?Ambrosio, M. Olivier, D. Didon, and C. Besche, “The basic empathy scale: A french validation of a measure of empathy in youth,” Personality and Individual Differences, vol. 46, no. 2, pp. 160–165, 2009. Google Scholar

  • [132] Y. Geng, D. Xia, and B. Qin, “The basic empathy scale: A chinese validation of ameasure ofempathy in adolescents,” Child Psychiatry & Human Development, vol. 43, no. 4, pp. 499–510, 2012. Google Scholar

  • [133] C. Bartneck, C. Rosalia, R. Menges, and I. Deckers, “Robot abuse—a limitation of the media equation,” in Proceedings of the interact 2005 workshop on agent abuse, Rome, 2005. Google Scholar

  • [134] C. Rosalia, R. Menges, I. Deckers, and C. Bartneck, “Cruelty towards robots,” in Robot Workshop-Designing Robot Applications for Everyday Use, Göteborg, 2005. Google Scholar

  • [135] C. Bartneck, M. Van Der Hoek, O. Mubin, and A. Al Mahmud, “Daisy, daisy, give me your answer do!: switching off a robot,” in Proceedings of the ACM/IEEE international conference on Human-robot interaction, pp. 217–222, ACM, 2007. Google Scholar

  • [136] L. Hall, “Inflicting pain on synthetic characters: Moral concerns and empathic interaction,” Virtual Social Agents, p. 144, 2005. Google Scholar

  • [137] A. M. Rosenthal-von der Pütten, N. C. Krämer, L. Hoffmann, S. Sobieraj, and S. C. Eimler, “An experimental study on emotional reactions towards a robot,” International Journal of Social Robotics, vol. 5, no. 1, pp. 17–34, 2013. Google Scholar

  • [138] C.-W. Chang, J.-H. Lee, P.-Y. Chao, C.-Y. Wang, and G.-D. Chen, “Exploring the possibility of using humanoid robots as instructional tools for teaching a second language in primary school.,” Educational Technology & Society, vol. 13, no. 2, pp. 13–24, 2010. Google Scholar

  • [139] T. Kanda, R. Sato, N. Saiwaki, and H. Ishiguro, “A two-month field trial in an elementary school for long-term human–robot interaction,” Robotics, IEEE Transactions on, vol. 23, no. 5, pp. 962–971, 2007. Google Scholar

  • [140] F. G. Phelps, G. Doherty-Sneddon, and H. Warnock, “Helping children think: Gaze aversion and teaching,” British Journal of Developmental Psychology, vol. 24, no. 3, pp. 577–588, 2006. Google Scholar

  • [141] S. Papert, Mindstorms: Children, computers, and powerful ideas. Basic Books, Inc., 1980. Google Scholar

  • [142] R. M. Gagné, The conditions of learning and theory of instruction. Holt, Rinehart and Winston New York, 1985. Google Scholar

  • [143] R. Azevedo and A. F. Hadwin, “Scaffolding self-regulated learning and metacognition–implications for the design of computer-based scaffolds,” Instructional Science, vol. 33, no. 5, pp. 367–379, 2005. CrossrefGoogle Scholar

  • [144] R. Ferguson, “The tripod project framework,” The Tripod Project, 2008. Google Scholar

  • [145] J. Ham, R. Bokhorst, R. Cuijpers, D. van der Pol, and J.-J. Cabibihan, “Making robots persuasive: the influence of combining persuasive strategies (gazing and gestures) by a storytelling robot on its persuasive power,” in Social Robotics, pp. 71–83, Springer, 2011. Google Scholar

  • [146] A. N. Meltzoff, “‘like me’: a foundation for social cognition,” Developmental science, vol. 10, no. 1, pp. 126–134, 2007. Google Scholar

  • [147] T. Salter, K. Dautenhahn, and R. Bockhorst, “Robots moving out of the laboratory-detecting interaction levels and human contact in noisy school environments,” in Robot and Human Interactive Communication, 2004. ROMAN 2004. 13th IEEE International Workshop on, pp. 563–568, IEEE, 2004. Google Scholar

  • [148] T. Kanda, M. Shiomi, Z. Miyashita, H. Ishiguro, and N. Hagita, “A communication robot in a shopping mall,” Robotics, IEEE Transactions on, vol. 26, no. 5, pp. 897–913, 2010. Google Scholar

About the article

Received: 2014-10-15

Accepted: 2015-04-02

Published Online: 2015-07-20


Citation Information: Paladyn, Journal of Behavioral Robotics, Volume 6, Issue 1, ISSN (Online) 2081-4836, DOI: https://doi.org/10.1515/pjbr-2015-0010.

Export Citation

© 2015 Stephane Lallee et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Gregoire Pointeau and Peter Ford Dominey
Frontiers in Neurorobotics, 2017, Volume 11
[2]
Maxime Petit, Tobias Fischer, and Yiannis Demiris
IEEE Transactions on Cognitive and Developmental Systems, 2016, Volume 8, Number 3, Page 201
[3]
Paul F. M. J. Verschure
Philosophical Transactions of the Royal Society B: Biological Sciences, 2016, Volume 371, Number 1701, Page 20150448
[4]
Stephane Lallee and Paul Verschure
Robotics, 2015, Volume 4, Number 2, Page 169

Comments (0)

Please log in or register to comment.
Log in