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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 1/2021

21-01-2021 | Technical Contribution

Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition

Authors: Matej Hoffmann, Shengzhi Wang, Vojtech Outrata, Elisabet Alzueta, Pablo Lanillos

Published in: KI - Künstliche Intelligenz | Issue 1/2021

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Abstract

Self-recognition or self-awareness is a capacity attributed typically only to humans and few other species. The definitions of these concepts vary and little is known about the mechanisms behind them. However, there is a Turing test-like benchmark: the mirror self-recognition, which consists in covertly putting a mark on the face of the tested subject, placing her in front of a mirror, and observing the reactions. In this work, first, we provide a mechanistic decomposition, or process model, of what components are required to pass this test. Based on these, we provide suggestions for empirical research. In particular, in our view, the way the infants or animals reach for the mark should be studied in detail. Second, we develop a model to enable the humanoid robot Nao to pass the test. The core of our technical contribution is learning the appearance representation and visual novelty detection by means of learning the generative model of the face with deep auto-encoders and exploiting the prediction error. The mark is identified as a salient region on the face and reaching action is triggered, relying on a previously learned mapping to arm joint angles. The architecture is tested on two robots with completely different face.
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Appendix
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Footnotes
1
Mitchell [46] discusses the “chicken-and-egg problem” of acquiring this self-image—prior recognition in the mirror may be necessary to learn it—and concludes that there are “three possibilities: (1) a visually based, incomplete self-image of the part of the organism it can see, (2) a non-visual self-image, (3) or a mixture of these images.”
 
2
Elbow pitch and wrist rotation were fixed.
 
Literature
1.
Abrossimoff J, Pitti A, Gaussier P (2018) Visual learning for reaching and body-schema with gain-field networks. In: 2018 Joint IEEE 8th international conference on development and learning and epigenetic robotics (ICDL-EpiRob). IEEE, pp 197–203
2.
Alzueta E, Melcón M, Jensen O, Capilla A (2019) The ‘Narcissus Effect’: top-down alpha-beta band modulation of face-related brain areas during self-face processing. NeuroImage 213:2020
3.
Alzueta E, Melcón M, Poch C, Capilla A (2019) Is your own face more than a highly familiar face? Biol Psychol 142:100–107
4.
Amsterdam B (1972) Mirror self-image reactions before age two. Dev Psychobiol 5(4):297–305
5.
Anderson JR (1984) The development of self-recognition: a review. Dev Psychobiol 17(1):35–49
6.
Anderson JR, Gallup GG (2015) Mirror self-recognition: a review and critique of attempts to promote and engineer self-recognition in primates. Primates 56(4):317–326
7.
Apps MAJ, Tsakiris M (2014) The free-energy self: a predictive coding account of self-recognition. Neurosci Biobehav Rev 41:85–97
8.
Asada M, Hosoda K, Kuniyoshi Y, Ishiguro H, Inui T, Yoshikawa Y, Ogino M, Yoshida C (2009) Cognitive developmental robotics: a survey. IEEE Trans Autonom Mental Dev 1(1):12–34
9.
Ballard Dana H (1987) Modular learning in neural networks. In AAAI, pp 279–284
10.
Bard KA, Todd BK, Bernier C, Love J, Leavens DA (2006) Self-awareness in human and chimpanzee infants: what is measured and what is meant by the mark and mirror test? Infancy 9(2):191–219
11.
Bigelow AE (1981) The correspondence between self-and image movement as a cue to self-recognition for young children. J Genet Psychol 139(1):11–26MathSciNet
12.
Bringsjord S, Licato J, Govindarajulu NS, Ghosh R, Sen A (2015) Real robots that pass human tests of self-consciousness. In: 2015 24th IEEE international symposium on robot and human interactive communication (RO-MAN). IEEE, pp 498–504
13.
Bruce V, Young A (1986) Understanding face recognition. Br J Psychol 77(3):305–327
14.
Cangelosi A, Schlesinger M (2015) Developmental robotics: from babies to robots. MIT Press, Cambridge
15.
Chang L, Fang Q, Zhang S, Poo M, Gong N (2015) Mirror-induced self-directed behaviors in rhesus monkeys after visual-somatosensory training. Curr Biol 25(2):212–217
16.
Chinn LK (2019) Development of Self Knowledge: Tactile Localization to Self-Recognition. PhD thesis, Tulane University School of Science and Engineering
17.
Corbetta M, Shulman GL (2002) Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 3(3):201–215
18.
Corbetta D, Thurman SL, Wiener RF, Guan Yu, Williams JL (2014) Mapping the feel of the arm with the sight of the object: on the embodied origins of infant reaching. Front Psychol 5:576
19.
de Waal Frans BM (2019) Fish, mirrors, and a gradualist perspective on self-awareness. PLoS Biol 17(2)
20.
De Waal F (2016) Are we smart enough to know how smart animals are?. WW Norton & Company, New York
21.
Diez-Valencia G, Ohashi T, Lanillos P, Cheng G (2019) Sensorimotor learning for artificial body perception. arXiv preprint arXiv:​1901.​09792
22.
Eimer M (2012) The face-sensitive N170 component of the event-related brain potential. Oxford Handbook of Face Perception, pp 329–344
23.
Fitzpatrick PM, Metta G (2002) Toward manipulation-driven vision. In Proc. IEEE/RSJ Int. Conf. on intelligent robots and systems
24.
Friston K (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 11(2):127
25.
Friston KJ, Daunizeau J, Kilner J, Kiebel SJ (2010) Action and behavior: a free-energy formulation. Biol Cybern 102(3):227–260
26.
Fuke S, Ogino M, Asada M (2007) Body image constructed from motor and tactle images with visual informaiton. Int J Hum Robot 4:347–364
27.
Gallagher S (2000) Philosophical conceptions of the self: implications for cognitive science. Trends Cogn Sci 4(1):14–21
28.
Gallup Jr GG (1982) Self-awareness and the emergence of mind in primates. Am J Primatol 2(3):237–248
29.
Gallup GG (1970) Chimpanzees: self-recognition. Science 167(3914):86–87
30.
Gold K, Scassellati B (2009) Using probabilistic reasoning over time to self-recognize. Robot Autonom Syst 57(4):384–392
31.
Guillaume P (1971) Imitation in children. trans. ep halperin
32.
Hafner VV, Loviken P, Villalpando AP, Schillaci G (2020) Prerequisites for an artificial self. Front Neurorobot:14
33.
Hart JW (2014) Robot self-modeling. Yale University, New Haven
34.
Heed T, Buchholz VN, Engel AK, Röder B (2015) Tactile remapping: from coordinate transformation to integration in sensorimotor processing. Trends Cogn Sci 19(5):251–258
35.
Hoffmann M, Pfeifer R (2018) Robots as powerful allies for the study of embodied cognition from the bottom up. In: Newen A, de Bruin L, Gallagher S (eds) The Oxford Handbook 4e Cognition, chapter 45. Oxford University Press, Oxford, pp 841–862
36.
Hoffmann M, Marques HG, Arieta AH, Sumioka H, Lungarella M, Pfeifer R (2010) Body schema in robotics: a review. Autonom Mental Dev IEEE Tran 2(4):304–324
37.
Ida Gobbini M, Haxby JV (2007) Neural systems for recognition of familiar faces. Neuropsychologia 45(1):32–41
38.
39.
Kuniyoshi Y (2019) Fusing autonomy and sociality via embodied emergence and development of behaviour and cognition from fetal period. Philos Trans R Soc B 374(1771):20180031
40.
Laflaquière A, Hafner VV (2019) Self-supervised body image acquisition using a deep neural network for sensorimotor prediction. In: 2019 Joint IEEE 9th international conference on development and learning and epigenetic robotics (ICDL-EpiRob). IEEE, pp 117–122
41.
Lanillos P, Dean-Leon E, Cheng G (2016) Yielding self-perception in robots through sensorimotor contingencies. IEEE Trans Cogn Dev Syst 9(2):100–112
42.
Lanillos P, Dean-Leon E, Cheng G (2017) Enactive self: a study of engineering perspectives to obtain the sensorimotor self through enaction. In: Joint IEEE Int. Conf. on, in developmental learning and epigenetic robotics
43.
Lanillos P, Pages J, Cheng G (2020) Robot self/other distinction: active inference meets neural networks learning in a mirror. In: European conference on artificial intelligence (ECAI 2020)
44.
Latinus M, Taylor MJ (2006) Face processing stages: impact of difficulty and the separation of effects. Brain Res 1123(1):179–187
45.
Ma K, Lippelt DP, Hommel B (2017) Creating virtual-hand and virtual-face illusions to investigate self-representation. JoVE 121:e54784
46.
Mitchell RW (1993) Mental models of mirror-self-recognition: two theories. New Ideas Psychol 11(3):295–325
47.
Natale L, Orabona F, Metta G, Sandini G (2007) Sensorimotor coordination in a “baby” robot: learning about objects through grasping. Prog Brain Res 164:403–424
48.
Neisser U (1988) Five kinds of self-knowledge. Philos Psychol 1(1):35–59
49.
50.
Pablo L, Emmanuel DL, Gordon C (2016) Multisensory object discovery via self-detection and artificial attention. In: Joint IEEE Int. Conf. on, In developmental learning and epigenetic robotics
51.
Pfeifer R, Bongard JC (2007) How the body shapes the way we think: a new view of intelligence. MIT Press, Cambridge
52.
Piaget J (1954) The construction of reality in the child. Basic Books, New York
53.
Pitti A, Mori H, Kouzuma S, Kuniyoshi Y (2009) Contingency perception and agency measure in visuo-motor spiking neural networks. IEEE Trans Autonom Mental Dev 1(1):86–97
54.
Prescott TJ, Camilleri D (2019) The synthetic psychology of the self. Cognitive architectures. Springer, Berlin, pp 85–104
55.
Rao RPN, Ballard DH (1999) Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat Neurosci 2(1):79–87
56.
Rood T, van Gerven M, Lanillos P (2020) A deep active inference model of the rubber-hand illusion. International Workshop on Active Inference. Springer, Cham, pp 84–91
57.
Sancaktar C, van Gerven M, Lanillos P (2020) End-to-end pixel-based deep active inference for body perception and action. In: Joint IEEE 10th international conference on development and learning and epigenetic robotics (ICDL-EpiRob)
58.
Schweinberger SR, Neumann MF (2016) Repetition effects in human ERPs to faces. Cortex 80:141–153
59.
Steels L, Spranger M (2008) The robot in the mirror. Connect Sci 20(4):337–358
60.
Sui J, Xiaosi G (2017) Self as object: emerging trends in self research. Trends Neurosci 40(11):643–653
61.
Tani J (1998) An interpretation of the ‘self’ from the dynamical systems perspective: a constructivist approach. J Conscious Stud 5(5–6):516–542
62.
Tsakiris M, Longo MR, Haggard P (2010) Having a body versus moving your body: neural signatures of agency and body-ownership. Neuropsychologia 48(9):2740–2749
63.
Yoshikawa Y, Tsuji Y, Hosoda K, Asada M (2004) Is it my body? body extraction from uninterpreted sensory data based on the invariance of multiple sensory attributes. In: 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS)(IEEE Cat. No. 04CH37566), vol 3. IEEE, pp 2325–2330
64.
Zaadnoordijk L, Besold TR, Hunnius S (2019) A match does not make a sense: on the sufficiency of the comparator model for explaining the sense of agency. Neurosci Conscious 1:niz006
65.
Metadata
Title
Robot in the Mirror: Toward an Embodied Computational Model of Mirror Self-Recognition
Authors
Matej Hoffmann
Shengzhi Wang
Vojtech Outrata
Elisabet Alzueta
Pablo Lanillos
Publication date
21-01-2021
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 1/2021
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-020-00701-7

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