Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Cognitive Architectures: The Dialectics of Agent/Environment Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

The Synthetic Psychology of the Self

verfasst von : Tony J. Prescott, Daniel Camilleri

Erschienen in: Cognitive Architectures

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Synthetic psychology describes the approach of “understanding through building” applied to the human condition. In this chapter, we consider the specific challenge of synthesizing a robot “sense of self”. Our starting hypothesis is that the human self is brought into being by the activity of a set of transient self-processes instantiated by the brain and body. We propose that we can synthesize a robot self by developing equivalent sub-systems within an integrated biomimetic cognitive architecture for a humanoid robot. We begin the chapter by motivating this work in the context of the criteria for recognizing other minds, and the challenge of benchmarking artificial intelligence against human, and conclude by describing efforts to create a sense of self for the iCub humanoid robot that has ecological, temporally-extended, interpersonal and narrative components set within a multi-layered model of mind.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Human Cognition-Inspired Robotic Grasping
Nächstes Kapitel Constructive Biology of Emotion Systems: First- and Second-Person Methods for Grounding Adaptation in a Biological and Social World
Fußnoten
1
By this, we mean the cluster of different but overlapping intellectual/cognitive faculties that make humans adaptive, flexible sociotechnical animals. Gardner’s [22] “multiple intelligences” view provides a good guide to this broader notion of human cognition. Attempts to create machine intelligence of this more multi-faceted form are increasingly discussed under the label Artificial General Intelligence (AGI) (e.g., [23]), hence we are using the phrase “general intelligence” rather than Gardner’s multiple intelligences.
 
2
Nathan Bateman to Caleb Smith about the humanoid robot “Ava” he has created, from the original movie script for Ex Machina (2015) by Alex Garland.
 
3
The suggestion that we call this the Garland test has also been made by Murray Shanahan, one of the scientific advisors on Ex Machina.
 
4
It has been suggested that Harnad’s T2 level cannot be achieved without first building T3 to achieve symbol-grounding [26]. Going directly to T2 is nevertheless a theoretical possibility, even if it might prove impossible to achieve without a contribution from robotics.
 
5
This idea also follows in the footsteps of many others. For example, the eighteenth century Neapolitan philosopher Giambattista Vico, who wrote “verum et factum reciprocantur seu convertuntur [the true is precisely what is made]”, and the 20th century physicist Richard Feynman, whose office blackboard on the day he died held the message, “what I cannot create I do not understand”.
 
6
There are multiple measures of so-called “correlates of consciousness”, Tononi’s Φ [65], a measure of information integration, being one of the better-known ones. The problem is that there is no way to be sure that an organism or machine that scores highly on any such measure is actually experiencing consciousness. This is known as the “other minds” problem in philosophy. For Turing [68], this was part of the reason to devise a behavioral test for the existence of machine thought and to leave the challenge of consciousness to others.
 
7
Abel’s “field of being” view stems from Merleau-Ponty’s [38] phenomenology and his insistence on the centrality of the experience of the body. Studies in cognitive neuroscience, such as those of the “rubber hand” illusion (see [10]), support Merleau-Ponty’s proposal that the sense of the body/self can extend into objects and the world. With virtual reality systems and telepresence robots, it is now possible to experimentally manipulate the sense of a virtual body, or of a physically remote robot body, and the associated feelings of immersion or “presence”, demonstrating that “my body is wherever there is something to be done” (Merleau-Ponty, [38] p. 291) and providing new ways to test hypotheses about the self.
 
8
This was proposed by Hume [30], for whom, if the stream of perceptions is turned off, as happens in sleep, the self ceases to exist, and by Locke [35], for whom self was a manifestation of consciousness, which, in turn, requires an awake mind. Some elements of Locke’s view of self, which saw identity as arising from learning and memory, are close to the ideas of the extended and narrative selves discussed in this chapter.
 
9
We should admit here that Strawson intends the more restricted philosophical sense of phenomenology as a form of systematic reflection on the structure of experience. We prefer to interpret the challenge of describing the nature of self from a more empirical perspective as phenomena associated with self that could be accessible to methods in psychology and cognitive neuroscience.
 
10
Note that, for a theory or concept of self to be useful, we would not consider that the self has to be emergent in a strong sense (that is, not reducible to lower level phenomena), but rather it has to serve a useful explanatory function in our psychological theory. In other words, the concept of self as explicated and realized in machine form should help us to provide useful accounts of human (or machine) cognition and behavior. See Verschure and Prescott [72] for a discussion of theory building and the role of synthetic approaches in the sciences of mind and brain.
 
11
Modularity is itself a topic that is widely debated within the cognitive sciences. Again, we consider that the synthetic approach can help answer some of the longstanding questions about how distributed vs. modular human minds/brains are. Our view is that the distributed nature of the brain can be over-stated. The brain is a layered architecture [49], and as such, there is significant replication of function and some redundancy across these layers, however, there is also localization of function and specific local or repeated circuits that perform roles that can be clearly described and differentiated.
 
12
Endel Tulving’s patient N.N. exemplifies this point [67]. A traffic accident caused N.N. to experience profound retrograde and anterograde amnesia, nevertheless he could still talk about himself, his experience, his preferences, and so on; he had intact short-term memory and could describe time and events in general terms. He could talk about consciousness, which he described as “being aware of who we are and what we are and where we are” ([67], p. 4). When asked to imagine what he might do tomorrow, however, his mind drew a blank, which he described as being “like swimming in the middle of a lake. There’s nothing there to do hold you up or do anything with” ([67], p. 4). Like other patients with amnesia, N.N. could be described as “marooned in the present” [34] or as having a self that has lost much of its “temporal thickness” [20].
 
Literatur
1.
Abel, C. (2014). The extended self: Architecture, memes and minds. Manchester: Manchester University Press.
2.
Amsterdam, B. (1972). Mirror self-image reactions before age two. Developmental Psychobiology, 5(4), 297–305.CrossRef
3.
4.
5.
Baron-Cohen, S., Leslie, A. M., & Frith, U. (1985). Does the autistic child have a ‘theory of mind’? Cognition, 21, 37–48.CrossRef
6.
Bauer, P. J. (2012). The life I once remembered: The waxing and waning of early memories. In D. Berntsen & D. C. Rubin (Eds.), Understanding autobiographical memory (pp. 205–225). Cambridge: CUP.CrossRef
7.
Bell, M. A., & Deater-Deckard, K. (2007). Biological systems and the development of self-regulation: Integrating behavior, genetics, and psychophysiology. Journal of Developmental & Behavioral Pediatrics, 28(5).
8.
Bermúdez, J. (1988). The paradox of self-consciousness. Cambridge, MA: MIT Press.
9.
Blakemore, S. (2003). Consciousness in meme machines. Journal of Consciousness Studies, 10(4–5), 19–30.
10.
Blakeslee, S., & Blakeslee, M. (2007). The body has a mind of its own. New York: Random House.
11.
Braitenberg, V. (1986). Vehicles: Experiments in synthetic psychology. Cambridge, MA: MIT Press.
12.
Camilleri, D., & Prescott, T. J. (2017). Action recognition with unsynchronised multi-sensory data. Paper presented at the 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB), Lisbon, Portugal.
13.
Camilleri, D., Damianou, A., Jackson, H., Lawrence, N., & Prescott, T. J. (2016). iCub visual memory inspector: Visualising the iCub’s thoughts. In N. F. Lepora, A. Mura, M. Mangan, P. F. M. J. Verschure, M. Desmulliez, & T. J. Prescott (Eds.), Biomimetic and Biohybrid Systems, the 5th International Conference on Living Machines (pp. 48–57). Berlin: Springer LNAI.
14.
Cangelosi, A., Schlesinger, M., & Smith, L. B. (2015). Developmental robotics: From babies to robots. Cambridge, MA: MIT Press.
15.
Damianou, A., Henrik, C., Boorman, L., Lawrence, N. D., & Prescott, T. J. (2015). A top-down approach for a synthetic autobiographical memory system. In S. Wilson, T. J. Prescott, A. Mura, & P. F. M. J. Verschure (Eds.), Biomimetic and Biohybrid Systems, the 4th International Conference on Living Machines (Vol. 9222, pp. 280–292). Berlin: Springer LNAI.
16.
Demiris, Y., Aziz-Zadeh, l., & Bonaiuto, J. (2014). Information processing in the mirror neuron system in primates and machines. Neuroinformatics, 12(1), 63–91.
17.
Doherty, M. (2009). Theory of mind: How children understand others’ thoughts and feelings. Hove: Psychology Press.
18.
Donald, M. (2012). Evolutionary origins of autobiographical memory: A retrieval hypothesis. In D. Berntsen & D. C. Rubin (Eds.), Understanding autobiographical memory (pp. 269–289). Cambridge: CUP.CrossRef
19.
Evans, M. H., Fox, C. W., & Prescott, T. J. (2014). Machines learning—towards a new synthetic autobiographical memory. In A. Duff, N. Lepora, A. Mura, T. Prescott, & P. M. J. Verschure (Eds.), Biomimetic and Biohybrid Systems, the 3rd International Conference on Living Machines (Vol. 8608, pp. 84–96). Berlin: Springer LNAI.
20.
Friston, K. (2017). The mathematics of mind-time. Aeon.
21.
Gallagher, S. (2000). Philosophical conceptions of the self: Implications for cognitive science. Trends in Cognitive Sciences, 4(1), 14–21.CrossRef
22.
Gardner, H. (2006). Multiple intelligences: New horizons. New York: Basic Books.
23.
Goertzel, B., & Pennachin, C. (2007). Artificial general intelligence. New York: Springer.CrossRef
24.
Harnad, S. (1991). Other bodies, other minds: A machine incarnation of an old philosophical problem. Minds and Machines, 1, 43–54.
25.
Harnad, S. (1994). Does the mind piggy-back on robotic and symbolic capacity? In H. L. Morowitz & J. L. Singer (Eds.), The mind, the brain, and complex adaptive systems, santa fe institute studies in complexity XXII (pp. 204–220). Boston: Addison Wesley.
26.
Hauser, L. (1993). Reaping the worldwind: Reply to harnad’s “other bodies, other minds”. Minds and Machines, 3, 219–238.CrossRef
27.
Hoffmann, M., Straka, Z., Farkas, I., Vavrecka, M., & Metta, G. (2017). Robotic homunculus: Learning of artificial skin representation in a humanoid robot motivated by primary somatosensory cortex. IEEE Transactions on Cognitive and Developmental Systems, pp(99), 1–1. https://​doi.​org/​10.​1109/​tcds.​2017.​2649225.
28.
Hofstadter, D. (2007). I am a strange loop. New York: Basic Books.MATH
29.
Hood, B. (2012). The Self illusion: Why there is no ‘you’ inside your head. London: Constable and Robinson.
30.
Hume, D. (1740). A treatise on human nature.
31.
32.
33.
Lambert, F. R., Lavenex, P., & Lavenex, P. B. (2017). The “when” and the “where” of single-trial allocentric spatial memory performance in young children: Insights into the development of episodic memory. Developmental Psychobiology, 59(2), 185–196. https://​doi.​org/​10.​1002/​dev.​21479.CrossRef
34.
Lidz, T. (1942). The amnesic syndrome. Archives of Neurology and Psychiatry, 47, 588–605.CrossRef
35.
Locke, J. (1777). An enquiry concerning human understanding.
36.
37.
Martinez-Hernandez, U., Damianou, A., Camilleri, D., Boorman, L. W., Lawrence, N., & Prescott, T. J. (2016). An integrated probabilistic framework for robot perception, learning and memory. Paper presented at the 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), Qingdao, China. pp. 1796–1801.
38.
Merleau-Ponty, M. (1945/1962). Phénoménologie de la Perception (C. Smith, Trans.). London: Routledge.
39.
Metzinger, T. (2009). The ego tunnel: The science of the mind and the myth of the self. New York: Basic Books.
40.
Mitchinson, B., Pearson, M., Pipe, T., & Prescott, T. J. (2011). Biomimetic robots as scientific models: A view from the whisker tip. In J. Krichmar & H. Wagatsuma (Eds.), Neuromorphic and brain-based robots (pp. 23–57). Boston, MA: MIT Press.CrossRef
41.
Moulin-Frier, C., Fischer, T., Petit, M., Pointeau, G., Puigbo, J. Y., & Pattacini, U., et al. (2017). DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self. IEEE Transactions on Cognitive and Developmental Systems, PP(99), 1–1. https://​doi.​org/​10.​1109/​tcds.​2017.​2754143.
42.
43.
Neisser, U. (1995). Criteria for an ecological self. In P. Rochat (Ed.), The Self in infancy: Theory and research. Amsterdam: Elsevier.
44.
Nelson, K. (2007). Young minds in social worlds: Experience, meaning and memory. Cambridge, MA: Harvard University Press.CrossRef
45.
Panksepp, J. (1998). Affective neuroscience: The foundations of human and animal emotions. Oxford: OUP.
46.
Pointeau, G., & Dominey, P. F. (2017). The role of autobiographical memory in the development of a robot self. Frontiers in Neurorobotics, 11, 27.CrossRef
47.
Prescott, T. J. (2007). Forced moves or good tricks in design space? Landmarks in the evolution of neural mechanisms for action selection. Adaptive Behavior, 15(1), 9–31.CrossRef
48.
Prescott, T. J. (2015). Me in the machine. New Scientist, 36–39.
49.
Prescott, T. J., Redgrave, P., & Gurney, K. N. (1999). Layered control architectures in robots and vertebrates. Adaptive Behavior, 7(1), 99–127.CrossRef
50.
Prescott, T. J., Mitchinson, B., Lepora, N. F., Wilson, S. P., Anderson, S. R., Porrill, J., et al. (2015). The robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics. In P. Krieger & A. Groh (Eds.), Sensorimotor integration in the whisker system (pp. 213–240). New York: Springer.CrossRef
51.
Prescott, T. J., Ayers, J., Grasso, F. W., & Verschure, P. F. M. J. (2016). Embodied models and neurorobotics. In M. A. Arbib & J. J. Bonaiuto (Eds.), From neuron to cognition via computational neuroscience (pp. 483–512). Cambridge, MA: MIT Press.
52.
Prescott, T. J., Lepora, N., & Verschure, P. F. M. J. (2018). The handbook of living machines: Research in biomimetic and biohybrid systems. Oxford, UK: OUP.
53.
Prior, H., Schwarz, A., & Gunturkun, O. (2008). Mirror-induced behavior in the magpie (Pica pica): Evidence of self-recognition. PLoS Biology, 6(8), e202.CrossRef
54.
Rochat, P. (2001). The infant’s world. Cambridge, MA: Harvard University Press.
55.
Roncone, A., Hoffmann, M., Pattacini, U., & Metta, G. (2014). Automatic kinematic chain calibration using artificial skin: Self-touch in the iCub humanoid robot. Paper presented at the 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 2305–2312.
56.
57.
Rubin, D. C. (2006). The basic-systems model of episodic memory. Perspectives on Psychological Science, 1(4), 277–311.CrossRef
58.
59.
Searle, J. (1990). Is the brain’s mind a computer program? Scientific American, 262(1), 20–25.CrossRef
60.
61.
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., & Guez, A., et al. (2017). Mastering chess and shogi by self-play with a general reinforcement learning algorithm. arXiv:​1712.​01815v1 [cs.AI] 5 Dec 2017.
62.
Strawson, G. (1997). The self. Journal of Consciousness Studies, 4(5/6), 405–428.
63.
64.
Tani, J. (1998). An interpretation of the ‘self’ from the dynamical systems perspective: A constructivist approach. Journal of Consciousness Studies, 5, 516–542.
65.
66.
67.
Tulving, E. (1985). Memory and consciousness. Canadian Journal of Psychology, 26(1), 1–12.CrossRef
68.
69.
70.
71.
72.
Verschure, P. F. M. J., & Prescott, T. J. (2018). A living machines approach to the sciences of mind and brain. In T. J. Prescott, N. Lepora, & P. F. M. J. Verschure (Eds.), The handbook of living machines: Research in biomimetic and biohybrid systems. Oxford, UK: OUP.
73.
Verschure, P. F. M. J., Krose, B., & Pfeifer, R. (1992). Distributed adaptive control: The self-organization of structured behavior. Robotics and Autonomous Systems, 9, 181–196.CrossRef
74.
Verschure, P. F. M. J., Pennartz, C. M. A., & Pezzulo, G. (2014). The why, what, where, when and how of goal-directed choice: Neuronal and computational principles. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 369(1655). https://​doi.​org/​10.​1098/​rstb.​2013.​0483.
75.
Metadaten
Titel
The Synthetic Psychology of the Self
verfasst von
Tony J. Prescott
Daniel Camilleri
Copyright-Jahr
2019
Buch
Cognitive Architectures

Print ISBN: 978-3-319-97549-8

Electronic ISBN: 978-3-319-97550-4

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-97550-4_7

Neuer Inhalt

    Bildnachweise