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The New Experimental Science of Physical Cognitive Systems

AI, Robotics, Neuroscience and Cognitive Sciences under a New Name with the Old Philosophical Problems?

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Book cover Philosophy and Theory of Artificial Intelligence

Part of the book series: Studies in Applied Philosophy, Epistemology and Rational Ethics ((SAPERE,volume 5))

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Abstract

It is likely that in AI, Robotics, Neuroscience and Cognitive Sciences, what we need is an integrated approach putting together concepts and methods from fields so far considered well distinct like non linear dynamics, information, computation and control theory as well as general AI, psychology, cognitive sciences in general, neurosciences and system biology. These disciplines usually share many problems, but have very different languages and experimental methodologies. It is thought that while tackling with many serious ‘hard core’ scientific issues it is imperative, probably a necessary (pre) requisite, that we do serious efforts to clarify and merge the underlying paradigms, the proper methodologies, the metrics and success criteria of this new branch of science. Many of these questions have already been approached by philosophy, but they acquire in this context a scientific nature: e.g.: Is it possible cognition without consciousness? And without ‘sentience’? In the context of AI and neuroscience research various definition of consciousness have been proposed (for example by Tononi, [44], to quote an example liked by the author). How they relate to the previous and contemporary philosophical analysis? Sometimes scientists may look as poor philosophers, and the opposite: philosophers may look as poor scientists, yet, the critical passages of history of science during a paradigm change or the birth of a new discipline have often involved a highly critical conceptual analysis intertwined with scientific and mathematical advancements. The scientific enterprise is now somehow close to unbundle the basic foundation of our consciousness and of our apperception of reality, and, it is clear that there are some circularity issues with the possible ‘explanations’, at least.

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References

  1. Wiener, N.: Cybernetics: or Control and Communication in the Animal and the Machine. MIT Press, Cambridge (1948)

    Google Scholar 

  2. Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  3. Merleau-Ponty, M.: Phenomenology of Perception (in French). Gallimard, Paris (1945)

    Google Scholar 

  4. Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Problems Inform. Transmission 1(1), 1–7 (1965)

    MathSciNet  Google Scholar 

  5. Chaitin, G.J.: On the length of programs for computing finite binary sequences: statistical considerations. J. Assoc. Comput. Mach. 16, 145–159 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  6. Hommel, B.: Becoming an intentional agent: The emergence of voluntary action. In: 5th eu Cognition Six Monthly Meeting euCognition, Munchen (2008)

    Google Scholar 

  7. Biro, S., Hommel, B. (eds.): Becoming an intentional agent: Early development of action interpretation and action control. Special issue of Acta Psychologica (2007)

    Google Scholar 

  8. Biro, S., Hommel, B.: Becoming an intentional agent: Introduction to the special issue. Acta Psychologica 124, 1–7 (2007)

    Article  Google Scholar 

  9. Hoffmann, J.: Anticipatory Behavioral Control. In: Butz, M.V., Sigaud, O., Gérard, P. (eds.) Anticipatory Behavior in Adaptive Learning Systems. LNCS (LNAI), vol. 2684, pp. 44–65. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Butz, M.V., Sigaud, O., Gérard, P.: Internal Models and Anticipations in Adaptive Learning Systems. In: Butz, M.V., Sigaud, O., Gérard, P. (eds.) Anticipatory Behavior in Adaptive Learning Systems. LNCS (LNAI), vol. 2684, pp. 86–109. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  11. George, D., Hawkins, J.: A hierarchical Bayesian model of invariant pattern recognition in the visual cortex. In: Proceedings of the International Joint Conference on Neural Net works. IEEE, Los Alamitos (2005)

    Google Scholar 

  12. Van Essen, D.C., Anderson, C.H., Felleman, D.J.: Information processing in the primate visual system: an integrated systems perspective. Science 255(5043), 419–423 (1992)

    Article  Google Scholar 

  13. Fukushima, K.: Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biological Cybernetics 36(4), 193–202 (1980)

    Article  MATH  Google Scholar 

  14. Hawkins, J., Blakeslee, S.: On Intelligence. Times Books, Henry Holt and Company (2004)

    Google Scholar 

  15. Lee, T.S., Mumford, D.: Hierarchical Bayesian inference in the visual cortex. J. Opt. Soc. Am. A. Opt. Image Sci. Vis. 20(7), 1434–1448 (2003)

    Article  Google Scholar 

  16. Pearl, J.: Probabilistic Reasoning in Intelligent Systems. MorganKaufman Publishers, San Francisco (1988)

    Google Scholar 

  17. Riesenhuber, M., Poggio, T.: Hierarchical models of object recognition in cortex. Nature Neuroscience 2(11), 1019–1025 (1999)

    Article  Google Scholar 

  18. Stringer, S.M., Rolls, E.T.: Invariant object recognition in the visual system with novel views of 3D objects. Neural Computation 14(11), 2585–2596 (2002)

    Article  MATH  Google Scholar 

  19. Bernardet, U., Bermudez i Badia, S., Verschure, P.F.M.J.: A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study. Theory in Biosciences 127 (2008)

    Google Scholar 

  20. Verschure, P.F.M.J.: Building a Cyborg: A Brain Based Architecture for Perception, Cognition and Action, Keynote talk. In: IROS 2008, Nice (2008)

    Google Scholar 

  21. Brooks, R.: A Robust Layered Control System for A Mobile Robot. IEEE Journal of Robotics and Automation (1986)

    Google Scholar 

  22. Pfeifer, R.: Cheap designs: exploiting the dynamics of the system-environment interaction. Three case studies on navigation. In: Conference on Prerational Intelligence — Pheno- monology of Complexity Emerging in Systems of Agents Interacting Using Simple Rules, Center for Interdisciplinary Research, University of Bielefeld, pp. 81–91 (1993)

    Google Scholar 

  23. Pfeifer, R., Iida, F.: Embodied Artificial Intelligence: Trends and Challenges. In: Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds.) Embodied Artificial Intelligence. LNCS (LNAI), vol. 3139, pp. 1–26. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  24. Lungarella, M., Iida, F., Bongard, J., Pfeifer, R. (eds.): 50 Years of AI. Springer, Heidelberg (2007)

    Google Scholar 

  25. Touchette, H., Lloyd, S.: Information-theoretic approach to the study of control systems. Physica A 331, 140–172 (2003)

    Article  MathSciNet  Google Scholar 

  26. Gomez, G., Lungarella, M., Tarapore, D.: Information-theoretic approach to embodied category learning. In: Proc. of 10th Int. Conf. on Artificial Life and Robotics, pp. 332–337 (2005)

    Google Scholar 

  27. Philipona, D., O’ Regan, J.K., Nadal, J.-P., Coenen, O.J.-M.D.: Perception of the structure of the physical world using unknown multimodal sensors and effectors. In: Advances in Neural Information Processing Systems (2004)

    Google Scholar 

  28. Olsson, L., Nehaiv, C.L., Polani, D.: Information Trade-Offs and the Evolution of Sensory Layouts. In: Proc. Artificial Life IX (2004)

    Google Scholar 

  29. Bonsignorio, F.P.: Preliminary Considerations for a Quantitative Theory of Networked Embodied Intelligence. In: Lungarella, M., Iida, F., Bongard, J.C., Pfeifer, R. (eds.) 50 Years of Aritficial Intelligence. LNCS (LNAI), vol. 4850, pp. 112–123. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  30. Burfoot, D., Lungarella, M., Kuniyoshi, Y.: Toward a Theory of Embodied Statistical Learning. In: Asada, M., Hallam, J.C.T., Meyer, J.-A., Tani, J. (eds.) SAB 2008. LNCS (LNAI), vol. 5040, pp. 270–279. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  31. Garcia, M., Chatterjee, A., Ruina, A., Coleman, M.: The Simplest Walking Model: Stability, Complexity, and Scaling, Transactions of the ASME. Journal of Biomechanical Engineering 120, 281–288 (1998)

    Article  Google Scholar 

  32. http://world.honda.com/ASIMO/technology/

  33. Lloyd, S.: Measures of Complexity: A Non exhaustive List. IEEE Control Systems Magazine (2001)

    Google Scholar 

  34. Rosenblatt, F.: The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain, Cornell Aeronautical Laboratory. Psychological Review 65(6), 386–408 (1958)

    Article  MathSciNet  Google Scholar 

  35. Potter, S.M.: What Can AI Get from Neuroscience? In: Lungarella, M., Iida, F., Bongard, J.C., Pfeifer, R. (eds.) 50 Years of Aritficial Intelligence. LNCS (LNAI), vol. 4850, pp. 174–185. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  36. Bach-y-Rita, P.: Brain Mechanisms in Sensory Substitution. Academic Press, New York (1972)

    Google Scholar 

  37. Der, R.: Self-organized acquisition of situated behavior. Theory in Biosciences 120, 179–187 (2001)

    Google Scholar 

  38. Der, R.: Artificial Life from the principle of homeokinesis. In: Proceedings of the German Workshop on Artificial Life (2008)

    Google Scholar 

  39. Prokopenko, M., Gerasimov, V., Tanev, I.: Evolving Spatiotemporal Coordination in a Modular Robotic System. In: Nolfi, S., Baldassarre, G., Calabretta, R., Hallam, J.C.T., Marocco, D., Meyer, J.-A., Miglino, O., Parisi, D. (eds.) SAB 2006. LNCS (LNAI), vol. 4095, pp. 558–569. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  40. Hornik, K., Stinchcombe, M., White, H.: Multilayer feedforward networks are universal approximators. Neural Networks 2, 359–366 (1989)

    Article  Google Scholar 

  41. Steels, L.: Semiotic dynamics for embodied agents. IEEE Intelligent Systems, 32–38 (2006)

    Google Scholar 

  42. Rus, D.L.: Robotics as Computation for Interaction with the Physical World. In: Special Session on CyberPhysical Systems. IEEE/RSJ 2008, Nice (2008)

    Google Scholar 

  43. Markus, G.F.: The Haphazard construction of the human mind. Houghton Mifflin, New York (2008)

    Google Scholar 

  44. Tononi, G.: Consciousness as integrated information: a provisional manifesto. Biological Bulletin 215, 216–242 (2008)

    Article  Google Scholar 

  45. Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A.A., Lally, A., Murdock, J.W., Nyberg, E., Prager, J., Schlaefer, N., Welty, C.: Building Watson: An Overview of the DeepQA Project. AI Magazine Fall (2010)

    Google Scholar 

  46. Berthoz, A.: The Brain’s sense of movement. Harvard University Press, Harvard (2000)

    Google Scholar 

  47. Amorim, M.A., Glasauer, S., Corpinot, K., Berthoz, A.: Updating an object’s orientation and location during non visual navigation: a comparison between two processing modes. Percept. Psychopys. 59, 404–418 (1997)

    Article  Google Scholar 

  48. Berthoz, A.: Neurobiology of "Umwelt" How Living Beings Perceive the World. In: Berthoz, A., Christen, Y. (eds.), Springer (2009)

    Google Scholar 

  49. Dodig-Crnkovic, G., Mueller, V.C.: A Dialogue Concerning Two World Systems: Info-Computational vs. Mechanistic, http://arxiv.org/abs/0910.5001

  50. Bonsignorio, F.P.: Steps to a Cyber-Physical Model of Networked Embodied Anticipatory Behavior. In: Pezzulo, G., Butz, M.V., Sigaud, O., Baldassarre, G. (eds.) ABiALS 2008. LNCS (LNAI), vol. 5499, pp. 77–94. Springer, Heidelberg (2009)

    Google Scholar 

  51. Amigoni, F., Reggiani, M., Schiaffonati, V.: An insightful comparison between experiments in mobile robotics and in science. Auton. Robots 27(4), 313–325 (2009)

    Article  Google Scholar 

  52. Chirikjian, G.S.: Information Theory on Lie-groups and Mobile Robotics Applications. In: Proceedings of ICRA 2010, Anchorage, AK (2010)

    Google Scholar 

  53. Chaumette, F., Hutchinson, S.: Visual Servoing and Tracking. In: Siciliano, B., Khatib, O. (eds.) Handbook of Robotics. Springer, Berlin (2008)

    Google Scholar 

  54. Nelissen, K., Luppino, G., Vanduffel, W., Rizzolatti, G., Orban, G.A.: Observing Others: Multiple Action Representation in the Frontal Lobe. Science 310(5746), 332–336 (2005)

    Article  Google Scholar 

  55. Wolpert, D.M., Diedrichsen, J., Flanagan, J.R.: Principles of sensorimotor learning. Nature Reviews Neuroscience 12, 739–751 (2011)

    Google Scholar 

  56. Rowe, T.B., Macrini, T.E., Luo, Z.: Fossil Evidence on Origin of the Mammalian Brain. Science 332(6032), 955–957 (2011)

    Article  Google Scholar 

  57. Pastra, K.: Personal communication (2010)

    Google Scholar 

  58. Bickhard, M.H., Terveen, L.: Foundational issues in artificial intelligence and cognitive science. Elsevier, Amsterdam (1995)

    Google Scholar 

  59. Shannon, C.E.: The Mathematical Theory of Communication. Bell Sys. Tech. J. 27, 623 (1948)

    MathSciNet  Google Scholar 

  60. http://www.robotcompanions.eu

  61. von Uexküll, J.: A Stroll Through the Worlds of Animals and Men: A Picture Book of Invisible Worlds. In: Schiller, C.H. (ed.) Instinctive Behavior: The Development of a Modern Concept, pp. 5–80. International Universities Press, Inc., New York (1957)

    Google Scholar 

  62. Damasio, A.: Descartes’ Error: Emotion, Reason, and the Human Brain, Putnam (1994)

    Google Scholar 

  63. Berthoz, A., Weiss, G.: Simplexity. Yale University Press, Yale (2012)

    Google Scholar 

  64. Einstein, A.: Obituary for physicist and philosopher Ernst Mach. Physikalische Zeitschrift 17 (1916)

    Google Scholar 

  65. Simon, H.: The architecture of complexity. Proc. Am. Phil. Soc. 106 (1962)

    Google Scholar 

  66. Ashby, W.R.: Design for a Brain. Chapman and Hill, London (1954)

    Google Scholar 

  67. Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  68. Eddington, A.S.: The Nature of the Physical World (1928)

    Google Scholar 

  69. Bateson, G.: Steps to an Ecology of Mind. University of Chicago Press, Chicago (1972)

    Google Scholar 

  70. Marx, K.: Capital, vol. I (in German), Hamburg (1867)

    Google Scholar 

  71. Kant, I.: Critique of Pure Reason (in German: Kritik der reinen Vernunft) (1781,1787)

    Google Scholar 

  72. Hume, D.: A Treatise of Human Nature: Being an Attempt to introduce the experimental Method of Reasoning into Moral Subjects (1739-1740)

    Google Scholar 

  73. Augustine of Hippo: Confessions (397-398)

    Google Scholar 

  74. Aristotle: Politics, Book 1, 1253b (322 BC)

    Google Scholar 

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Authors and Affiliations

  1. University Carlos III of Madrid and Heron Robots, Madrid, Spain

    Fabio Bonsignorio

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  1. Fabio Bonsignorio
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Editors and Affiliations

  1. and University of Oxford, Anatolia College/ACT, Pylaia, 55510, Greece

    Vincent C. Müller

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Bonsignorio, F. (2013). The New Experimental Science of Physical Cognitive Systems. In: Müller, V. (eds) Philosophy and Theory of Artificial Intelligence. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31674-6_10

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  • DOI: https://doi.org/10.1007/978-3-642-31674-6_10

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