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Embodied Artificial Intelligence: Trends and Challenges

  • Rolf Pfeifer
  • Fumiya Iida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3139)

Abstract

The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from “theoretically stable”, a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this non-technical paper we briefly characterize the field, summarize its achievements, and identify important issues for future research. One of the fundamental unresolved problems has been and still is how thinking emerges from an embodied system. Provocatively speaking, the central issue could be captured by the question “How does walking relate to thinking?”

Keywords

Humanoid Robot Ubiquitous Computing Artificial Life Grand Challenge Genetic Regulatory Network 
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. Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds.): Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 130–145. Springer, Heidelberg (2004)Google Scholar
  2. Ballard, D.: Artificial Intelligence, 48th edn., pp. 57–86 (1991)Google Scholar
  3. Banzhaf, W.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 284–292. Springer, Heidelberg (2004)Google Scholar
  4. Boblan, I., Bannasch, R., Schwenk, H., Miertsch, L., Schulz, A.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  5. Bellot, D., Siegwart, R., Bessiere, P., Tapus, A., Coue, C., Diard, J.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 186–201. Springer, Heidelberg (2004)Google Scholar
  6. Blickhan, R., Wagner, H., Seyfarth, A.: Brain or muscles?, Rec. Res. Devel. Bio-mechanics 1, 215–245 (2003)Google Scholar
  7. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm intelligence: from natural to artificial systems. Oxford University Press, New York (1999)MATHGoogle Scholar
  8. Bongard, J.C.: Incremental approaches to the combined evolution of a robot’s body andbrain. Unpublished PhD thesis. Faculty of Mathematics and Science, University of Zurich (2003)Google Scholar
  9. Bongard, J.C.: Evolving modular genetic regulatory networks. In: Proc. IEEE 2002Congress on Evolutionary Computation (CEC2002), pp. 305–311. MIT Press, Cambridge (2002)Google Scholar
  10. Bongard, J.C., Pfeifer, R.: Repeated structure and dissociation of genotypic and phenotypic complexity in artificial ontogeny. In: Spector, L., et al. (eds.) Proc. of the Sixth European Conference on Artificial Life, pp. 401–412 (2001)Google Scholar
  11. Brooks, R.A.: Intelligence Without Reason. Proceedings of the 12th International Joint Conference on Artificial Intelligence (IJCAI 1991), pp. 569-595 (1991)Google Scholar
  12. Brooks, R.A., Stein, L.A.: Building brains for bodies. In: Memo 1439, Artificial Intelligence Lab, MIT, Cambridge (1993)Google Scholar
  13. Collins, S.H., Wisse, M., Ruina, A.: A three-dimensional passive-dynamic walking robot with two legs and knees. The International Journal of Robotics Research 20 ,607615 (2001)Google Scholar
  14. Dipellegrino, G., Fadiga, L., Fogassi, L., Gallese, V., Rizzolatti, G.: Understanding motorevents - a neuro-physiological study. Exp. Brain Res. 91, 176–180 (1992)Google Scholar
  15. Edelman, G.E.: Bright air, brilliant fire. In: On the matter of the mind, BasicBooks, New York (1992)Google Scholar
  16. Eggenberger, P.: Evolving morphologies of simulated 3d organisms based on differential gene expression. In: Husbands, P., Harvey, I. (eds.) Proc. of the 4th European Conference on Artificial Life, MIT Press, Cambridge (1997)Google Scholar
  17. Eggenberger, P.: Evolution of three-dimensional, artificial organisms: simulations of developmental processes. Unpublished PhD Dissertation, Medical Faculty, University of Zurich, Switzerland (1999)Google Scholar
  18. Elman, J.L., Bates, E.A., Johnson, H.A., Karmiloff-Smith, A., Parisi, D., Plunkett, K.: Rithinking innateness: A connectionist perspective on development. MIT Press, Cambridge (1996)Google Scholar
  19. Epstein, J.M., Axtell, R.L.: Growing artificial societies: social science from the bottom up. MIT Press, Cambridge (1996)Google Scholar
  20. Fadiga, L., Fogassi, L., Gallese, V., Rizzolatti, G.: Visuomotor neurons: Ambiguity of the discharge or ’motor’ perception? Int. J. Psychophysiol 35, 165–177 (2000)CrossRefGoogle Scholar
  21. Ferber, J.: Multi-agent systems. Introduction to distributed artificial intelligence. Addison-Wesley (1999)Google Scholar
  22. Floreano, D., Mondada, F., Perez-Uribe, A., Roggen, D.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  23. Gallese, V., Fadiga, L., Fogassi, L., Rizzolatti, G.: Action recognition in the pre-motor cortex. Brain 119, 593–60 (1996)Google Scholar
  24. Gaussier, P., Prepin, K., Nadel, J.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  25. Gomez, G., Lungarella, M., Eggenberger Hotz, P., Matsushita, K., Pfeifer, R.: Simulating development in a real robot: on the concurrent increase of sensory, motor, and neural complexity. In: The 4th annual workshop of Epigenetic Robotics, EPIROBOT 2004 (2004) (in press)Google Scholar
  26. Hafner, V.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  27. Hara, F., Pfeifer, R. (eds.): Morpho-functional machines: the new species - designing embodied intelligence. Springer, Tokyo (2003)Google Scholar
  28. Hara, F., Pfeifer, R.: On the relation among morphology, material and control in morpho-functional machines. In: Meyer, B., Floreano, R., Wilson (eds.) From Animals to Animats 6. Proceedings of the sixth International Conference on Simulation of Adaptive Behavior 2000, pp. 33–40 (2000)Google Scholar
  29. Holland, O.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  30. Hosoda, K.: Robot finger design for developmental tactile interaction. In: Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds.) Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 219–230. Springer, Heidelberg (2004)Google Scholar
  31. Iida, F., Pfeifer, R.: Cheap Rapid locomotion of a quadruped robot: Self-stabilization of bounding gait. In: Groesn, F., et al. (eds.) Intelligent Autonomous Systems 8, pp. 642–649. IOS Press, Amsterdam (2004)Google Scholar
  32. Iida, F., Pfeifer, R.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004b)Google Scholar
  33. Ishiguro, A., Kawakatsu, T.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2003)Google Scholar
  34. Janssen, B., de Boer, B., Belpaeme, T.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  35. Kaplan, F., Oudeyer, P.-Y.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  36. Kubow, T.M., Full, R.J.: The role of the mechanical system in control: a hypothesis of self-stabilization in hexapedal runners. Phil. Trans. R. Soc. Lond. B 354, 849–861 (1999)CrossRefGoogle Scholar
  37. Kuniyoshi, Y., Yorozu, Y., Ohmura, Y., Terada, K., Otani, T., Nagakubo, A., Yamamoto, T.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  38. Lambrinos, D., Moller, R., Labhart, T., Pfeifer, R., Wehner, R.: A mobile robot employing insect strategies for navigation. Robotics and Autonomous Systems 30, 39–64 (2000)CrossRefGoogle Scholar
  39. Lenat, D., Prakash, M., Shepher, M.: CYC: Using common sense knowledge to overcome brittleness and knowledge acquistion bottlenecks. AI Magazine 6(4), 65–85 (1986)Google Scholar
  40. Langton, C.G.: Artificial life: an overview. MIT Press, Cambridge (1995)Google Scholar
  41. Lipson, H., Pollack, J.B.: Automatic design and manufacture of artificial life forms. Nature 406, 974–978 (2000)CrossRefGoogle Scholar
  42. Lichtensteiger, L.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  43. Lungarella, M., Berthouze, L.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  44. Lungarella, M., Pfeifer, R.: Information-theoretic analysis of sensory-motor data. In: Proc. of the IEEE-RAS International Conference on Humanoid Robots, pp. 245–252 (2001)Google Scholar
  45. Lungarella, M., Metta, G., Pfeifer, R., Sandini, G.: Developmental robotics: a survey. Connection Science 15(4), 151–190 (2003)CrossRefGoogle Scholar
  46. Mead, C.A.: Analog VLSI and neural systems. Addison-Wesley, Reading (1989)MATHGoogle Scholar
  47. Murata, S., Kamimura, A., Kurokawa, H., Yoshida, E., Tomita, K., Kokaji, S.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  48. Nagai, Y., Hosoda, K., Asada, M.: Joint attention emerges through bootstrap learning. In: Proc. of the 2003 IEEE/RSJ International Conference on Intelligent Robots andSystems (IROS 2003), pp. 168–173 (2003)Google Scholar
  49. Nolfi, S., Floreano, D.: Evolutionary robotics: the biology, intelligence, and technology of self-organizing machines. MIT Press, Cambridge, MA (2001)Google Scholar
  50. Nunez, R.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  51. Okada, M., Nakamura, D., Nakamura, Y.: On-line and hierarchical design methods of dynamics based information processing system. In: Proc. of the 2003 IEEE/RJS Int. Conference on Intelligent Robots and Systems, pp. 954–959 (2003)Google Scholar
  52. Pfeifer, R.: On the role of embodiment in the emergence of cognition and emotion. In: Hatano, H., Okada, N., Tanabe, H. (eds.) Affective minds, pp. 43–57. Elsevier, Amsterdam (2000)Google Scholar
  53. Pfeifer, R., Iida, F., Bongard, J.: New robotics: design principles for intelligent systems. Artificial Life (2004) (in press)Google Scholar
  54. Pfeifer, R., Scheier, C.: Understanding intelligence. MIT Press, Cambridge (1999)Google Scholar
  55. Rechenberg, I.: Evolution strategies: optimization of technical systems with principles from biological evolution. Frommann-Holzboog, Germany (1973) (in German)Google Scholar
  56. Sims, K.: Evolving virtual creatures. Computer Graphics 28, 15–34 (1994a)CrossRefGoogle Scholar
  57. Sporns, O., Pegors, T.K.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  58. Steels, L.: Language games for autonomous agents. IEEE Intelligent Systems ,September/October issues(2001)Google Scholar
  59. Steels, L.: Evolving grounded communication for robots. Trends in Cognitive Sciences 7(7), 308–312 (2003)CrossRefGoogle Scholar
  60. Steels, L.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  61. Te Boekhorst, R., Lungarella, M., Pfeifer, R.: Dimensionality reduction through sensory-motor coordination. In: Kaynak, O., Alpaydın, E., Oja, E., Xu, L. (eds.) ICANN 2003 and ICONIP 2003. LNCS, vol. 2714, pp. 496–503. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  62. Thelen, E., Smith, L.: A dynamic systems approach to the development of cognition and action. MIT Press, Cambridge (1994)Google Scholar
  63. Thompson, A.: Silicon evolution. In: Koza, J.R., et al. (eds.) Genetic Programming 1996: Proc. of the First Annual Conference, pp. 444–452. MIT Press, Cambridge (1996)Google Scholar
  64. Webb, B., Consi, R.C.: Biorobotics -Methods & application. MIT Press, Cambridge (2000)Google Scholar
  65. Weiser, M.: Hot topics: Ubiquitous computing. IEEE Computer Society Press, Los Alamitos (1993)Google Scholar
  66. Wisse, M., van Frankenhuyzen, J.: Design and Construction of MIKE; a 2D autonomous biped based on passive dynamic walking. In: Proceedings of the 2nd International Symposium on Adaptive Motion of Animals and Machines, Kyoto, March 4-8 (2003)Google Scholar
  67. Yamamoto, T., Kuniyoshi, Y.: Harnessing the robot’s body dynamics: a global dynamics approach. In: Proc. of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2001), Hawaii, USA, pp. 518–525 (2001)Google Scholar
  68. Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds.): Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  69. Yoshikawa, Y., Asada, M., Hosoda, K.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar
  70. Ziemke, T.: Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139. Springer, Heidelberg (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Rolf Pfeifer
    • 1
  • Fumiya Iida
    • 1
  1. 1.Artificial Intelligence Laboratory, Department of InformaticsUniversity of ZurichZurichSwitzerland

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