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AI in the 21st Century – With Historical Reflections

  • Max Lungarella
  • Fumiya Iida
  • Josh C. Bongard
  • Rolf Pfeifer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4850)

Abstract

The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program – a set of algorithms to process symbols – has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face.

Keywords

Home Appliance Dartmouth College Semiotic System Internet Search Engine Natural Intelligence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Wiener, N.: Cybernetics or Control and Communication in the Animal and the Machine. MIT Press, Cambridge, MA (1948)Google Scholar
  2. 2.
    Walter, G.W.: An imitation of life. Scientific American 182(5), 42–45 (1950)CrossRefGoogle Scholar
  3. 3.
    Turing, A.M.: Computing machinery and intelligence. Mind 59(236), 433–460 (1950)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Legg, S., Hutter, M.: Tests of machine intelligence. LNCS, vol. 4850. Springer, Heidelberg (2007)Google Scholar
  5. 5.
    McCorduck, P.: Machines Who Think, 2nd edn. A.K. Peters Ltd., Natick, MA (2003)Google Scholar
  6. 6.
    Schmidhuber, J.: 2006: Celebrating 75 years of AI – history and outlook: the next 25 years. LNCS, vol. 4850. Springer, Heidelberg (2006)Google Scholar
  7. 7.
    Brooks, R.A.: The relationship between matter and life. Nature 409, 409–411 (2001)CrossRefGoogle Scholar
  8. 8.
    Nilsson, N.: The physical symbol system hypothesis: status and prospects. LNCS, vol. 4850. Springer, Heidelberg (2007)Google Scholar
  9. 9.
    Steels, L.: Fifty years of AI: from symbols to embodiment – and back. LNCS, vol. 4850. Springer, Heidelberg (2007)Google Scholar
  10. 10.
    Brooks, R.A.: New approaches to robotics. Science 253, 1227–1232 (1991)CrossRefGoogle Scholar
  11. 11.
    Chiel, H., Beer, R.: The brain has a body: adaptive behavior emerges from interactions of nervous system, body, and environment. Trends in Neurosciences 20, 553–557 (1997)CrossRefGoogle Scholar
  12. 12.
    Clark, A.: Being There – Putting Brain, Body, and World Together Again. MIT Press, Cambridge, MA (1997)Google Scholar
  13. 13.
    Pfeifer, R., Scheier, C.: Understanding Intelligence. MIT Press, Cambridge, MA (1999)Google Scholar
  14. 14.
    Pfeifer, R., Bongard, J.C.: How the Body Shapes the Way we Think – A New View of Intelligence. MIT Press, Cambridge, MA (2007)Google Scholar
  15. 15.
    Varela, F.J., Thompson, E., Rosch, E.: The Embodied Mind. MIT Press, Cambridge, MA (1991)Google Scholar
  16. 16.
    Iida, F., Pfeifer, R., Seyfarth, A.: AI in locomotion: challenges and perspectives of underactuated robots. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  17. 17.
    Nehaniv, C.L., Mirza, N.A., Olsson, L.: Development via information self-structuring of sensorimotor experience and interaction. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  18. 18.
    Pfeifer, R., Lungarella, M., Sporns, O., Kuniyoshi, Y.: On the information theoretic implications of embodiment – principles and methods. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  19. 19.
    Polani, D., Sporns, O., Lungarella, M.: How information and embodiment shape intelligent information processing. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  20. 20.
    Dautenhahn, K.: A paradigm shift in artificial intelligence: why social intelligence matters in the design and development of robots with human-like intelligence. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  21. 21.
    Huelse, M., Wischmann, S., Manoonpong, P., von Twickel, A., Pasemann, F.: Dynamical systems in the sensorimotor loop: on the interrelation between internal and external mechanisms of evolved robot behavior. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  22. 22.
    Kaplan, F., Oudeyer, P.-Y.: Intrinsically motivated machines. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  23. 23.
    Lungarella, M., Metta, G., Pfeifer, R., Sandini, G.: Developmental robotics: a survey. Connection Science 15(4), 151–190 (2003)CrossRefGoogle Scholar
  24. 24.
    Lungarella, M.: Developmental robotics, Scholarpedia, p. 173175 (2007)Google Scholar
  25. 25.
    Lipson, H.: Curious and creative machines. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  26. 26.
    Froese, T.: On the role of AI in the ongoing paradigm shift within the cognitive sciences. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  27. 27.
    Boblan, I., Bannasch, R., Schulz, A., Schwenk, H.: A human-like robot torso ZAR5 with fluidic muscles: toward a common platform for embodied AI. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  28. 28.
    Behkam, B., Sitti, M.: Bacteria integrated swimming robots. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  29. 29.
    Potter, S.: What can AI get from neuroscience? LNCS, vol. 4850. Springer, Heidelberg (2007)Google Scholar
  30. 30.
    Arbib, M., Metta, G., van der Smagt, P.: Neurorobotics: from vision to action. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics – ch. 63, Springer, BerlinGoogle Scholar
  31. 31.
    Fattori, P., Breveglieri, R., Nicoletta, M., Maniadakis, M., Galletti, C.: Brain area V6A: a cognitive model for an embodied artificial intelligence. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  32. 32.
    O’Regan, K.J.: How to build consciousness into a robot: the sensorimotor approach. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  33. 33.
    Vernon, D., Furlong, D.: Philosophical foundations of enactive AI. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  34. 34.
    Kitano, H.: Systems biology: a brief overview. Science 295(2002), 1662–1664 (2002)CrossRefGoogle Scholar
  35. 35.
    Lungarella, M., Sporns, O.: PLoS Comp. Biol., e144 (2006)Google Scholar
  36. 36.
    Bongard, J.C., Zykov, V., Lipson, H.: Resilient machines through continuous self-modeling. Science 314, 1118–1121 (2006)CrossRefGoogle Scholar
  37. 37.
    Bonsignorio, F.P.: Preliminary considerations for a quantitative theory of networked embodied intelligence. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  38. 38.
    Hernandez-Arieta, A., Kato, R., Yu, W., Yokoi, H.: The man-machine interaction: FMRI study for an EMG prosthetic hand with biofeedback. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar
  39. 39.
    Clark, A.: Re-inventing ourselves: the plasticity of embodiment, sensing, and mind. J. of Medicine and Philosophy 32, 263–282 (2007)CrossRefGoogle Scholar
  40. 40.
    Lebedev, M.A., Nicolelis, M.A.L.: Brain-machine interfaces: past, present, and future. Trends in Neurosciences 29, 536–546 (2006)CrossRefGoogle Scholar
  41. 41.
    Weibel, A., Bernardin, K., Woelfel, M.: Computer-supported human-human multilingual communication. LNCS, vol. 4850. Springer, Heidelberg (2007) Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Max Lungarella
    • 1
  • Fumiya Iida
    • 2
  • Josh C. Bongard
    • 3
  • Rolf Pfeifer
    • 1
  1. 1.Dept. of Informatics, University of ZurichSwitzerland
  2. 2.Computer Science and Artificial Intelligence Lab, MITUSA
  3. 3.Dept. of Computer Science, University of VermontUSA

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