Skip to main content

Part of the book series: Springer Handbooks ((SHB))

Abstract

Embodied intelligence is the computational approach to the design and understanding of intelligent behavior in embodied and situated agents through the consideration of the strict coupling between the agent and its environment (situatedness), mediated by the constraints of the agent’s own body, perceptual and motor system, and brain (embodiment). The emergence of the field of embodied intelligence is closely linked to parallel developments in computational intelligence and robotics, where the focus is on morphological computation and sensory–motor coordination in evolutionary robotics models, and in neuroscience and cognitive sciences where the focus is on embodied cognition and developmental robotics models of embodied symbol learning. This chapter provides a theoretical and technical overview of some principles of embodied intelligence, namely morphological computation, sensory–motor coordination, and developmental embodied cognition. It will also discuss some tutorial examples on the modeling of body/brain/environment adaptation for the evolution of morphological computational agents, evolutionary robotics model of navigation and object discrimination, and developmental robotics models of language and numerical cognition in humanoid robots.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 269.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 349.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

ACP:

active categorical perception

DOF:

degree of freedom

EC:

embodied cognition

OM:

operational momentum

RGB:

red-green-blue

RT:

reaction time

SNARC:

spatial–numerical association of response code

SOM:

self-organizing map

References

  1. R.D. Beer: A dynamical systems perspective on agent-environment interaction, Artif. Intell. 72, 173–215 (1995)

    Article  Google Scholar 

  2. R.A. Brooks: Elephants don't play chess, Robot. Auton. Syst. 6(1), 3–15 (1990)

    Article  Google Scholar 

  3. A. Cangelosi: Grounding language in action and perception: From cognitive agents to humanoid robots, Phys. Life Rev. 7(2), 139–151 (2010)

    Article  Google Scholar 

  4. H.J. Chiel, R.D. Beer: The brain has a body: Adaptive behavior emerges from interactions of nervous system, body and environment, Trends Neurosci. 20, 553–557 (1997)

    Article  Google Scholar 

  5. F. Keijzer: Representation and Behavior (MIT Press, London 2001)

    Google Scholar 

  6. S. Nolfi, D. Floreano: Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines (MIT/Bradford Books, Cambridge 2000)

    Google Scholar 

  7. R. Pfeifer, J.C. Bongard: How the Body Shapes the Way We Think: A New View of Intelligence (MIT Press, Cambridge 2006)

    Google Scholar 

  8. C. Paul: Morphology and computation, Proc. Int. Conf. Simul. Adapt. Behav. (2004) pp. 33–38

    Google Scholar 

  9. C. Paul: Morphological computation: A basis for the analysis of morphology and control requirements, Robot. Auton. Syst. 54(8), 619–630 (2006)

    Article  Google Scholar 

  10. R. Pfeifer, F. Iida: Morphological computation: Connecting body, brain and environment, Jpn. Sci. Mon. 58(2), 48–54 (2005)

    Google Scholar 

  11. G. Pezzulo, L.W. Barsalou, A. Cangelosi, M.H. Fischer, K. McRae, M.J. Spivey: The mechanics of embodiment: A dialog on embodiment and computational modeling, Front. Psychol. 2(5), 1–21 (2011)

    Google Scholar 

  12. D. Pecher, R.A. Zwaan (Eds.): Grounding Cognition: The Role of Perception and Action in Memory, Language, and Thinking (Cambridge Univ. Press, Cambridge 2005)

    Google Scholar 

  13. M. Wilson: Six views of embodied cognition, Psychon. Bull. Rev. 9, 625–636 (2002)

    Article  Google Scholar 

  14. L. Meteyard, S.R. Cuadrado, B. Bahrami, G. Vigliocco: Coming of age: A review of embodiment and the neuroscience of semantics, Cortex 48(7), 788–804 (2012)

    Article  Google Scholar 

  15. R. Shepard, J. Metzler: Mental rotation of three dimensional objects, Science 171(972), 701–703 (1972)

    Google Scholar 

  16. K. Dijkstra, M.P. Kaschak, R.A. Zwaan: Body posture facilitiates the retrieval of autobiographical memories, Cognition 102, 139–149 (2007)

    Article  Google Scholar 

  17. L.E. Williams, J.A. Bargh: Keeping one's distance: The influence of spatial distance cues on affect and evaluation, Psychol. Sci. 19, 302–308 (2008)

    Article  Google Scholar 

  18. A. Cangelosi, M. Schlesinger: Developmental Robotics: From Babies to Robots (MIT Press, Cambridge 2012)

    Google Scholar 

  19. J. Bongard: The utility of evolving simulated robot morphology increases with task complexity for object manipulation, Artif. Life 16(3), 201–223 (2010)

    Article  Google Scholar 

  20. E. Tuci, G. Massera, S. Nolfi: Active categorical perception of object shapes in a simulated anthropomorphic robotic arm, IEEE Trans. Evol. Comput. 14(6), 885–899 (2010)

    Article  Google Scholar 

  21. R. Pfeifer, G. Gomez: Morphological computation – Connecting brain, body, and environment, Lect. Notes Comput. Sci. 5436, 66–83 (2009)

    Article  Google Scholar 

  22. V. Pavlov, A. Timofeyev: Construction and stabilization of programmed movements of a mobile robot-manipulator, Eng. Cybern. 14(6), 70–79 (1976)

    Google Scholar 

  23. S. Hirose, Y. Umetani: The development of soft gripper for the versatile robot hand, Mech. Mach. Theor. 13(3), 351–359 (1978)

    Article  Google Scholar 

  24. E. Brown, N. Rodenberg, J. Amend, A. Mozeika, E. Steltz, M.R. Zakin, H. Lipson, H.M. Jaeger: Universal robotic gripper based on the jamming of granular material, Proc. Natl. Acad. Sci. USA 107(44), 18809–18814 (2010)

    Article  Google Scholar 

  25. T.J. Allen, R.D. Quinn, R.J. Bachmann, R.E. Ritzmann: Abstracted biological principles applied with reduced actuation improve mobility of legged vehicles, Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. 2 (2003) pp. 1370–1375

    Google Scholar 

  26. M. Wisse, G. Feliksdal, J. Van Frankkenhuyzen, B. Moyer: Passive-based walking robot, IEEE Robot. Autom. Mag. 14(2), 52–62 (2007)

    Article  Google Scholar 

  27. K. Sims: Evolving 3d morphology and behavior by competition, Artif. Life 1(4), 353–372 (1994)

    Article  Google Scholar 

  28. J.E. Auerbach, J.C. Bongard: On the relationship between environmental and morphological complexity in evolved robots, Proc. 14th Int. Conf. Genet. Evol. Comput. (2012) pp. 521–528

    Google Scholar 

  29. GECCO 2012 Robot Videos: https://www.youtube.com/playlist?list=PLD5943A95ABC2C0B3

  30. J.E. Auerbach, J.C. Bongard: On the relationship between environmental and mechanical complexity in evolved robots, Proc. 13th Int. Conf. Simul. Synth. Living Syst. (2012) pp. 309–316

    Google Scholar 

  31. F. Mondada, E. Franzi, P. Ienne: Mobile robot miniaturisation: A tool for investigation in control algorithms, Proc. 3rd Int. Symp. Exp. Robot. (Kyoto, Japan 1993)

    Google Scholar 

  32. S. Nolfi: Power and limits of reactive agents, Neurocomputing 49, 119–145 (2002)

    Article  MATH  Google Scholar 

  33. C. Scheier, R. Pfeifer, Y. Kunyioshi: Embedded neural networks: Exploiting constraints, Neural Netw. 11, 1551–1596 (1998)

    Article  Google Scholar 

  34. S. Nolfi: Categories formation in self-organizing embodied agents. In: Handbook of Categorization in Cognitive Science, ed. by H. Cohen, C. Lefebvre (Elsevier, Amsterdam 2005) pp. 869–889

    Chapter  Google Scholar 

  35. J.J. Gibson: The Perception of the Visual World (Houghton Mifflin, Boston 1950)

    Google Scholar 

  36. N. Franceschini, F. Ruffier, J. Serres, S. Viollet: Optic flow based visual guidance: From flying insects to miniature aerial vehicles. In: Aerial Vehicles, ed. by T.M. Lam (InTech, Rijeka 2009)

    Google Scholar 

  37. S. Nolfi, D. Marocco: Active perception: A sensorimotor account of object categorization. In: From Animals to Animats 7, (MIT Press, Cambridge 2002) pp. 266–271

    Google Scholar 

  38. D. Floreano, T. Kato, D. Marocco, S. Sauser: Coevolution of active vision and feature selection, Biol. Cybern. 90(3), 218–228 (2004)

    Article  MATH  Google Scholar 

  39. H.A. Ruff: Infants' manipulative exploration of objects: Effect of age and object characteristics, Dev. Psychol. 20, 9–20 (1984)

    Article  Google Scholar 

  40. R. Bajcsy: Active perception, Proc. IEEE 76(8), 996–1005 (1988)

    Article  Google Scholar 

  41. D.H. Ballard: Animate vision, Artif. Intell. 48, 57–86 (1991)

    Article  Google Scholar 

  42. J. De Greef, S. Nolfi: Evolution of implicit and explicit communication in a group of mobile robots. In: Evolution of Communication and Language in Embodied Agents, ed. by S. Nolfi, M. Mirolli (Springer, Berlin 2010)

    Google Scholar 

  43. J.L. Elman, E.A. Bates, M. Johnson, A. Karmiloff-Smith, D. Parisi, K. Plunkett: Rethinking Innateness: A Connectionist Perspective on Development (MIT Press, Cambridge 1996)

    Google Scholar 

  44. S. Nolfi, D. Floreano: Learning and evolution, auton, Robots 7(1), 89–113 (1999)

    Article  Google Scholar 

  45. N. Bernstein: The Coordination and Regulation of Movements (Pergamon, Oxford 1967)

    Google Scholar 

  46. P. Savastano, S. Nolfi: Incremental learning in a 14 DOF simulated iCub robot: Modelling infant reach/grasp development, Lect. Notes Comput. Sci. 7375, 369–370 (2012)

    Article  Google Scholar 

  47. A.M. Collins, M.R. Quillian: Retrieval time from semantic memory, J. Verb. Learn. Verb. Behav. 8, 240–247 (1969)

    Article  Google Scholar 

  48. E. Rosch: Cognitive representations of semantic categories, J. Exp. Psychol. Gen. 104, 192–233 (1975)

    Article  Google Scholar 

  49. D.E. Rumelhart, J.L. McClelland, P.D.P. Group: Parallel Distributed Processing: Explorations in the microstructure of Cognition (MIT Press, Cambridge 1986)

    Google Scholar 

  50. S. Harnad: The symbol grounding problem, Physica D 42, 335–346 (1990)

    Article  Google Scholar 

  51. L.W. Barsalou: Grounded cognition, Annu. Rev. Psychol. 59, 617–645 (2008)

    Article  Google Scholar 

  52. M. Asada, K. Hosoda, Y. Kuniyoshi, H. Ishiguro, T. Inui, Y. Yoshikawa, M. Ogino, C. Yoshida: Cognitive developmental robotics: A survey, IEEE Trans. Auton. Mental Dev. 1, 12–34 (2009)

    Article  Google Scholar 

  53. M. Lungarella, G. Metta, R. Pfeifer, G. Sandini: Developmental robotics: A survey, Connect Sci. 15(4), 151–190 (2003)

    Article  Google Scholar 

  54. P.Y. Oudeyer: Developmental robotics. In: Encyclopedia of the Sciences of Learning, Springer References Series, ed. by N.M. Seel (Springer, New York 2012) p. 329

    Google Scholar 

  55. A. Glenberg, K. Kaschak: Grounding language in action, Psychon. Bull. Rev. 9(3), 558–565 (2002)

    Article  Google Scholar 

  56. M.H. Fischer, R.A. Zwaan: Embodied language – A review of the role of the motor system in language comprehension, Q. J. Exp. Psychol. 61(6), 825–850 (2008)

    Article  Google Scholar 

  57. F. Pulvermüller: The Neuroscience of Language (Cambridge Univ. Press, Cambridge 2003)

    Book  Google Scholar 

  58. S.F. Cappa, D. Perani: The neural correlates of noun and verb processing, J. Neurolinguist. 16(2/3), 183–189 (2003)

    Article  Google Scholar 

  59. O. Hauk, I. Johnsrude, F. Pulvermüller: Somatotopic representation of action words in human motor and premotor cortex, Neuron 41(2), 301–330 (2004)

    Article  Google Scholar 

  60. M. Tomasello: Constructing a Language (Harvard Univ. Press, Cambridge 2003)

    Google Scholar 

  61. L.B. Smith, L. Samuelson: Objects in space and mind: From reaching to words. In: Thinking Through Space: Spatial Foundations of Language and Cognition, ed. by K. Mix, L.B. Smith, M. Gasser (Oxford Univ. Press, Oxford 2010)

    Google Scholar 

  62. A.F. Morse, T. Belpaeme, A. Cangelosi, L.B. Smith: Thinking with your body: Modelling spatial biases in categorization using a real humanoid robot, 2010 Annu. Meet. Cogn. Sci. Soc. (2010) pp. 33–38

    Google Scholar 

  63. G. Metta, L. Natale, F. Nori, G. Sandini, D. Vernon, L. Fadiga, C. von Hofsten, J. Santos-Victor, A. Bernardino, L. Montesano: The iCub humanoid robot: An open-systems platform for research in cognitive development, Neural Netw. 23, 1125–1134 (2010)

    Article  Google Scholar 

  64. A.F. Morse, J. de Greeff, T. Belpaeme, A. Cangelosi: Epigenetic robotics architecture (ERA), IEEE Trans. Auton. Mental Dev. 2(4), 325–339 (2010)

    Article  Google Scholar 

  65. Y. Sugita, J. Tani: Learning semantic combinatoriality from the interaction between linguistic and behavioral processes, Adapt. Behav. 13(1), 33–52 (2005)

    Article  Google Scholar 

  66. V. Tikhanoff, A. Cangelosi, G. Metta: Language understanding in humanoid robots: iCub simulation experiments, IEEE Trans. Auton. Mental Dev. 3(1), 17–29 (2011)

    Article  Google Scholar 

  67. E. Tuci, T. Ferrauto, A. Zeschel, G. Massera, S. Nolfi: An experiment on behavior generalization and the emergence of linguistic compositionality in evolving robots, IEEE Trans. Auton. Mental Dev. 3(2), 176–189 (2011)

    Article  Google Scholar 

  68. Y. Yamashita, J. Tani: Emergence of functional hierarchy in a multiple timescale neural network model: A humanoid robot experiment, PLoS Comput. Biol. 4(11), e1000220 (2008)

    Article  Google Scholar 

  69. L. Steels: Modeling the cultural evolution of language, Phys. Life Rev. 8(4), 339–356 (2011)

    Article  Google Scholar 

  70. L. Steels: Experiments in Cultural Language Evolution, Advances in Interaction Studies, Vol. 3 (John Benjamins, Amsterdam 2012)

    Book  Google Scholar 

  71. F. Stramandinoli, D. Marocco, A. Cangelosi: The grounding of higher order concepts in action and language: A cognitive robotics model, Neural Netw. 32, 165–173 (2012)

    Article  Google Scholar 

  72. J. Piaget: The Origins of Intelligence in Children (International Univ. Press, New York 1952)

    Book  Google Scholar 

  73. G.J. Groen, J.M. Parkman: A chronometric analysis of simple addition, Psychol. Rev. 79(4), 329–343 (1972)

    Article  Google Scholar 

  74. R.S. Moyer, T.K. Landauer: Time required for judgements of numerical inequality, Nature 215, 1519–1520 (1967)

    Article  Google Scholar 

  75. M. Rucinski, A. Cangelosi, T. Belpaeme: An embodied developmental robotic model of interactions between numbers and space, Expanding the Space of Cognitive Science, 23rd Annu. Meet. Cogn. Sci. Soc., ed. by L. Carlson, C. Hoelscher, T.F. Shipley (Cognitive Science Society, Austin 2011) pp. 237–242

    Google Scholar 

  76. S. Dehaene, S. Bossini, P. Giraux: The mental representation of parity and number magnitude, J. Exp. Psychol. Gen. 122, 371–396 (1993)

    Article  Google Scholar 

  77. G. Wood, H.C. Nuerk, K. Willmes, M.H. Fischer: On the cognitive link between space and number: A meta-analysis of the SNARC effect, Psychol. Sci. Q. 50(4), 489–525 (2008)

    Google Scholar 

  78. M.H. Fischer, A.D. Castel, M.D. Dodd, J. Pratt: Perceiving numbers causes spatial shifts of attention, Nat. Neurosci. 6(6), 555–556 (2003)

    Article  Google Scholar 

  79. D.B. Berch, E.J. Foley, R. Hill, R.P. McDonough: Extracting parity and magnitude from Arabic numerals: Developmental changes in number processing and mental representation, J. Exp. Child Psychol. 74, 286–308 (1999)

    Article  Google Scholar 

  80. M.H. Fischer: Finger counting habits modulate spatial-numerical associations, Cortex 44, 386–392 (2008)

    Article  Google Scholar 

  81. S.M. Göbel, S. Shaki, M.H. Fischer: The cultural number line: A review of cultural and linguistic influences on the development of number processing, J. Cross-Cult. Psychol. 42, 543–565 (2011)

    Article  Google Scholar 

  82. S. Shaki, M.H. Fischer: Reading space into numbers – A cross-linguistic comparison of the SNARC effect, Cognition 108, 590–599 (2008)

    Article  Google Scholar 

  83. S. Shaki, M.H. Fischer, W.M. Petrusic: Reading habits for both words and numbers contribute to the SNARC effect, Psychon. Bull. Rev. 16(2), 328–331 (2009)

    Article  Google Scholar 

  84. M.H. Fischer, R. Mills, S. Shaki: How to cook a SNARC: Number placement in text rapidly changes spatial-numerical associations, Brain Cogn. 72, 333–336 (2010)

    Article  Google Scholar 

  85. M.H. Fischer, P. Brugger: When digits help digits: Spatial-numerical associations point to finger counting as prime example of embodied cognition, Front. Psychol. 2, 260 (2011)

    Article  Google Scholar 

  86. M. Pinhas, M.H. Fischer: Mental movements without magnitude? A study of spatial biases in symbolic arithmetic, Cognition 109, 408–415 (2008)

    Article  Google Scholar 

  87. M. Rucinski, A. Cangelosi, T. Belpaeme: Robotic model of the contribution of gesture to learning to count, Proc. IEEE ICDL-EpiRob Conf. Dev. (2012)

    Google Scholar 

  88. Q. Chen, T. Verguts: Beyond the mental number line: A neural network model of number-space interactions, Cogn. Psychol. 60(3), 218–240 (2010)

    Article  Google Scholar 

  89. D. Caligiore, A.M. Borghi, D. Parisi, G. Baldassarre: TRoPICALS: A computational embodied neuroscience model of compatibility effects, Psychol. Rev. 117, 1188–1228 (2010)

    Article  Google Scholar 

  90. D. Caligiore, A.M. Borghi, R. Ellis, A. Cangelosi, G. Baldassarre: How affordances associated with a distractor object can cause compatibility effects: A study with the computational model TRoPICALS, Psychol. Res. 77(1), 7–19 (2013)

    Article  Google Scholar 

  91. O. Lindemann, A. Alipour, M.H. Fischer: Finger counting habits in Middle-Eastern and Western individuals: An online survey, J. Cross-Cult. Psychol. 42, 566–578 (2011)

    Article  Google Scholar 

  92. M.W. Alibali, A.A. DiRusso: The function of gesture in learning to count: More than keeping track, Cogn. Dev. 14(1), 37–56 (1999)

    Article  Google Scholar 

  93. R. Pfeifer, M. Lungarella, F. Iida: The challenges ahead for bio-inspired `soft' robotics, Commun. ACM 55(11), 76–87 (2012)

    Article  Google Scholar 

  94. M. Lungarella, O. Sporns: Information self-structuring: Key principle for learning and development, Proc. 4th Int. Conf. Dev. Learn. (2005)

    Google Scholar 

  95. P. Capdepuy, D. Polani, C. Nehaniv: Maximization of potential information flow as a universal utility for collective behaviour, Proc. 2007 IEEE Symp. Artif. Life (CI-ALife 2007) (2007) pp. 207–213

    Chapter  Google Scholar 

  96. L. Gleitman: The structural sources of verb meanings, Lang. Acquis. 1, 135–176 (1990)

    Article  Google Scholar 

  97. J. Mayor, K. Plunkett: Vocabulary explosion: Are infants full of Zipf?, Proc. 32nd Annu. Meet. Cogn. Sci. Soc., ed. by S. Ohlsson, R. Catrambone (Cognitive Science Society, Austin 2010)

    Google Scholar 

  98. E. Thelen, L.B. Smith: A Dynamic Systems Approach to the Development of Cognition and Action (MIT Press, Cambridge 1994)

    Google Scholar 

  99. M.L. McKinney, K.J. McNamara: Heterochrony, the Evolution of Ontogeny (Plenum, New York 1991)

    Google Scholar 

  100. A. Cangelosi: Heterochrony and adaptation in developing neural networks, Proc. GECCO99 Genet. Evol. Comput. Conf., ed. by W. Banzhaf (Morgan Kaufmann, San Francisco 1999) pp. 1241–1248

    Google Scholar 

  101. G.C. Hinton, S.J. Nowlan: How learning can guide evolution, Complex Syst. 1, 495–502 (1987)

    MATH  Google Scholar 

  102. S. Nolfi, J.L. Elman, D. Parisi: Learning and evolution in neural networks, Adapt. Behav. 3(1), 5–28 (1994)

    Article  Google Scholar 

  103. J. Bongard: Morphological change in machines accelerates the evolution of robust behavior, Proc. Natl. Acad. Sci. USA 108(4), 1234–1239 (2011)

    Article  Google Scholar 

  104. S. Kumar, P. Bentley (Eds.): On Growth, Form, and Computers (Academic, London 2003)

    Google Scholar 

  105. K.O. Stanley, R. Miikkulainen: A taxonomy for artifcial embryogeny, Artif. Life 9, 93–130 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Angelo Cangelosi or Josh Bongard .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Cangelosi, A., Bongard, J., Fischer, M.H., Nolfi, S. (2015). Embodied Intelligence. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-43505-2_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43504-5

  • Online ISBN: 978-3-662-43505-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics