Advertisement

Paladyn

, Volume 1, Issue 2, pp 99–108 | Cite as

Toward psycho-robots

  • Andrei Yu. KhrennikovEmail author
Research Article
  • 23 Downloads

Abstract

We try to perform geometrization of psychology by representing mental states, “ideas,” by points of a metric space-mental space. Evolution of ideas is described by dynamical systems in metric mental space. We apply the mental space approach for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1–4, we consider cognitive systems with increasing complexity of psychological behavior determined by the structure of flows of ideas. Since our models are in fact models of the AI-type, one immediately recognizes that they can be used for creation of AI-systems, which we call psycho-robots, exhibiting important elements of the human psyche. Creation of such psycho-robots may be useful in the improvement of domestic robots. At the moment domestic robots are merely simple working devices (e.g. vacuum cleaners or lawn mowers). However, in future one can expect demand for systems which can not only perform simple work tasks, but also have elements of human self-developing psyche. Such AI-psyche could play an important role both in relations between psycho-robots and their owners as well as between psycho-robots. Since the presence of a huge numbers of psycho-complexes is an essential characteristic of human psychology, it would be interesting to model them in the AI-framework.

Keywords

mental space dynamical systems conscious/unconscious flows of information psychoanalysis complexes symptoms hidden forbidden wishes desires repression resistance force modeling of psyche psycho-robots 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    P. Gay, Freud: A life for our time. W.W. Norton, NY, 1988.Google Scholar
  2. [2]
    V. Green, Emotional Development in Psychoanalysis, Attachment Theory and Neuroscience: Creating Connections, Routledge, 2003.Google Scholar
  3. [3]
    M. Macmillan, The Completed Arc: Freud Evaluated. MIT Press., Cambridge MA, 1997.Google Scholar
  4. [4]
    M. Solms and O. Turnbull, The Brain and the InnerWorld: An Introduction to the Neuroscience of Subjective Experience. New York, Other Press, 2003.Google Scholar
  5. [5]
    M. Solms, An Introduction to the Neuroscientific Works of Freud. In The Pre-Psychoanalytic Writings of Sigmund Freud. Eds.: G. van der Vijver and F. Geerardyn. Karnac, London, 25–26, 2002.Google Scholar
  6. [6]
    M. Solms, Putting the psyche into neuropsychology. Psychologist 19(9), 538–539, 2006.Google Scholar
  7. [7]
    M. Solms, Sigmund Freud today. Psychoanalysis and neuroscience in dialogue. Psyche-Zeiteschrift fur Psychoanalyse und ihre Anwendungen 60(9–10), 829–859, 2006.Google Scholar
  8. [8]
    D. J. Stein, M. Solms, J. van Honk, The cognitive-affective neuroscience of the unconscious. CNS Spectrums 11(8), 580–583, 2006.Google Scholar
  9. [9]
    E. Young-Bruehl, Subject to Biography. Harvard University Press, Boston, 1998.Google Scholar
  10. [10]
    A. Yu. Khrennikov, Non-Archimedean analysis: quantum paradoxes, dynamical systems and biological models. Kluwer, Dordrecht, 1997.zbMATHGoogle Scholar
  11. [11]
    A. Yu. Khrennikov, Human subconscious as the P-adic dynamical system. J. of Theor. Biology 193, 179–196, 1998.CrossRefGoogle Scholar
  12. [12]
    A. Yu. Khrennikov, P-adic dynamical systems: description of concurrent struggle in biological population with limited growth. Dokl. Akad. Nauk 361, 752, 1998.zbMATHMathSciNetGoogle Scholar
  13. [13]
    A. Yu. Khrennikov, Description of the operation of the human subconscious by means of P-adic dynamical systems. Dokl. Akad. Nauk 365, 458–460, 1999.zbMATHMathSciNetGoogle Scholar
  14. [14]
    A. Yu. Khrennikov, P-adic discrete dynamical systems and collective behaviour of information states in cognitive models. Discrete Dynamics in Nature and Society 5, 59–69, 2000.CrossRefGoogle Scholar
  15. [15]
    A. Yu. Khrennikov, Classical and quantum mechanics on P-adic trees of ideas. BioSystems 56, 95–120, 2000.CrossRefGoogle Scholar
  16. [16]
    A.Yu. Khrennikov, Classical and quantum mental models and Freud’s theory of unconscious mind. Series Math. Modelling in Phys., Engineering and Cognitive sciences, 1. Växjö Univ. Press, Växjö, 2002.Google Scholar
  17. [17]
    S. Albeverio, A. Yu. Khrennikov, P. Kloeden, Memory retrieval as a p-adic dynamical system. Biosystems 49, 105–115, 1999.CrossRefGoogle Scholar
  18. [18]
    D. Dubischar, V. M. Gundlach, O. Steinkamp, A. Khrennikov, A padic model for the process of thinking disturbed by physiological and information noise, J. Theor. Biology, 197, 451–467, 1999.CrossRefGoogle Scholar
  19. [19]
    A.Yu. Khrennikov, Information dynamics in cognitive, psychological, social, and anomalous phenomena. Kluwer, Dordreht, 2004.zbMATHGoogle Scholar
  20. [20]
    A. Yu. Khrennikov, Probabilistic pathway representation of cognitive information. J. Theor. Biology 231, 597–613, 2004.CrossRefGoogle Scholar
  21. [21]
    N. Chomsky, Formal properties of grammas. Handbook of mathematical psychology. Luce, R. D.; Bush, R.R.; Galanter, E.; Eds. 2, Wiley: New York, pp. 323–418, 1963.Google Scholar
  22. [22]
    P. S. Churchland, T. Sejnovski, The computational brain. MITP: Cambridge, 1992.Google Scholar
  23. [23]
    M. A. Boden, Mind as Machine — A History of Cognitive Science. Oxford, UK: Oxford University Press. Boden, M. A, 1998, Creativity and Artificial Intelligence. Artificial Intelligence 103(1–2): 347–356, 2006.Google Scholar
  24. [24]
    M. A. Boden, Artificial Genius. Discover 17: 104–107, 1996.Google Scholar
  25. [25]
    C. G. Langton, C. Taylor, J. D. Farmer, S. Rasmussen (Eds), Artificial Life-2, pp.41–91, Redwood City, CA, Addison Wesley, 1992.Google Scholar
  26. [26]
    C. G. Langton, Life at the edge of chaos. In: C. G. Langton, C. Taylor, J.D. Farmer, S. Rasmussen (Eds), Artificial Life-2. Redwood City, CA, Addison Wesley, 1992.Google Scholar
  27. [27]
    R. J. Collings, D. R. Jefferson, AntFarm: Towards simulated evolution. In: C. G. Langton, C. Taylor, J.D. Farmer, S. Rasmussen (Eds), Artificial Life-2, pp. 579–601. Redwood City, CA, Addison Wesley, 1992.Google Scholar
  28. [28]
    L. Yaeger, Computational genetics, physiology, metabolism, neural systems, learning, vision, and behavior or Polyworld: Life in a new context. In: Artificial Life-3, pp. 263–298. Redwood City, CA, Addison Wesley, 1994.Google Scholar
  29. [29]
    J. Y. Donnart and J. A. Meyer, Learning reactive and planning rules in a motivationally autonomous animat. IEEE Trans. Systems, Man., and Cybernetics. Part B: Cybernetics, 26, N 3, pp. 381–395, 1996.CrossRefGoogle Scholar
  30. [30]
    J.-A. Meyer, A. Guillot, From SAB90 to SAB94: Four years of Animat research. In: Proc. of the Third International Conference of Adaptive Behavior. Cambridge: The MIT Press, 1994.Google Scholar
  31. [31]
    R. Ashby, Design of a brain. Chapman-Hall, London, 1952.Google Scholar
  32. [32]
    C. Eliasmith, The third contender: a critical examination of the dynamicist theory of cognition. Phil. Psychology 9(4), 441–463, 1996.CrossRefGoogle Scholar
  33. [33]
    S. H. Strogatz, Nonlinear dynamics and chaos with applications to physics, biology, chemistry, and engineering. Addison Wesley, Reading, Mass, 1994.Google Scholar
  34. [34]
    T. van Gelder, R. Port, It’s about time: Overview of the dynamical approach to cognition. in Mind as motion: Explorations in the dynamics of cognition. Ed.: T. van Gelder, R. Port. MITP, Cambridge, Mass, 1–43, 1995.Google Scholar
  35. [35]
    T. van Gelder, What might cognition be, if not computation? J. of Philosophy 91, 345–381, 1995.CrossRefGoogle Scholar
  36. [36]
    G. M. Edelman, The remembered present: a biological theory of consciousness. New York, Basic Books, 1989.Google Scholar
  37. [37]
    J. A. Fodor and Z. W. Pylyshyn, Connectionism and cognitive architecture: a critical analysis, Cognition, 280, 3–17, 1988.CrossRefGoogle Scholar
  38. [38]
    Voronkov, G.S., 2002a. Information and brain: viewpoint of neurophysiolog. Neurocomputers: development and applications N 1–2, 79–88.Google Scholar
  39. [39]
    S. Freud, New introductory lectures on psychoanalysis. New York, Penguin Books, 1962.Google Scholar
  40. [40]
    S. Freud, Two short accounts of psycho-analysis. New York, Penguin Books, 1962.Google Scholar
  41. [41]
    S. Freud, The interpretation of dreams. Standard Edition, 4 and 5, 1900.Google Scholar
  42. [42]
    V. Potkonjak, J. Radojicic, S. Tzafestas, Modeling Robot “Psycho- Physical” State and Reactions — A New Option in Human-Robot Communication Part 1: Concept and Background Journal of Intelligent and Robotic Systems, 35, 339–352, 2002.Google Scholar
  43. [43]
    R. Brooks, C. Breazeal, M. Marjanovic, B. Scassellati, M. Williamson, The Cog Project: Building a Humanoid Robot. In Computation for Metaphors, Analogy and Agents, 1562, Springer Lecture Notes in Artificial Intelligence, Springer-Verlag. pp. 8–13, 1998.Google Scholar
  44. [44]
    R. A. Brooks, C. Breazeal (Ferrell), R. Irie, C. C. Kemp, M. Marjanovic, B. Scassellati, M. Williamson, Alternate Essences of Intelligence. AAAI-98, 1998.Google Scholar
  45. [45]
    R. A. Brooks, Cambrian Intelligence, The Early History of the New AI. Cambridge, MA: The MIT Press, pp. 8–9, 1999.zbMATHGoogle Scholar
  46. [46]
    R. A. Brooks, Flesh and Machines, How Robots Will Change Us. New York: Pantheon Books, p. 65, 2002.Google Scholar
  47. [47]
    T. L. Manuel, Creating a Robot Culture: An Interview with Luc Steels. IEEE Intelligent Systems, 18(3),59–61 May/June, 2003.CrossRefGoogle Scholar

Copyright information

© © Versita Warsaw and Springer-Verlag Wien 2010

Authors and Affiliations

  1. 1.Center for Mathematical Modeling in Physics and Cognitive SciencesLinnaeus UniversityLinnaeusSweden

Personalised recommendations