How Virtual Machinery Can Bridge the “Explanatory Gap”, in Natural and Artificial Systems

  • Aaron Sloman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6226)


We can now show in principle how evolution could have produced the “mysterious” aspects of consciousness if, like engineers in the last six or seven decades, it had to solve increasingly complex problems of representation and control by producing systems with increasingly abstract, but effective, mechanisms, including self-observation capabilities, implemented in non-physical virtual machines which, in turn, are implemented in lower level physical mechanisms. For this, evolution would have had to produce far more complex virtual machines than human engineers have so far managed, but the key idea might be the same. However it is not yet clear whether the biological virtual machines could have been implemented in the kind of discrete technology used in computers as we know them.


Virtual Machine Causal Power Physical Machine Mental Phenomenon Phenomenal Consciousness 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Arbib, M.A.: Rana computatrix to Human Language: Towards a Computational Neuroethology of Language Evolution. Philosophical Transactions: Mathematical, Physical and Engineering Sciences 361(1811), 2345–2379 (2003)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Baars, B.J.: A cognitive Theory of Consciousness. CUP, Cambridge (1988)Google Scholar
  3. 3.
    Block, N.: On a confusion about the function of consciousness. Behavioral and Brain Sciences 18, 227–247 (1995)CrossRefGoogle Scholar
  4. 4.
    Chalmers, D.J.: Facing Up to the Problem of Consciousness. Journal of Consciousness Studies 2(3), 200–219 (1995)MathSciNetGoogle Scholar
  5. 5.
    Chalmers, D.J.: The Conscious Mind: In Search of a Fundamental Theory. OUP, New York (1996)zbMATHGoogle Scholar
  6. 6.
    Craik, K.: The Nature of Explanation. CUP, London (1943)Google Scholar
  7. 7.
    Dennett, D.C.: Consciousness Explained. Penguin, London (1991)Google Scholar
  8. 8.
    Dyson, G.B.: Darwin Among The Machines: The Evolution of Global Intelligence. Addison-Wesley, Reading (1997)Google Scholar
  9. 9.
    Gibson, E.J., Pick, A.D.: An Ecological Approach to Perceptual Learning and Development. OUP, New York (2000)Google Scholar
  10. 10.
    Huxley, T.H.: Lessons in Elementary Physiology. MacMillan & Co., New York (1866)Google Scholar
  11. 11.
    Jablonka, E., Lamb, M.J.: Evolution in Four Dimensions. MIT Press, Cambridge (2005)Google Scholar
  12. 12.
    Kim, J.: Mind in a Physical World. MIT Press, Cambridge (1998)Google Scholar
  13. 13.
    McGinn, C.: Consciousness and Its Objects. OUP, Oxford (2004)CrossRefGoogle Scholar
  14. 14.
    Nagel, T.: What is it like to be a bat. In: Hofstadter, D., Dennett, D.C. (eds.) The Mind’s I: Fantasies and Reflections on Self and Soul, pp. 391–403. Penguin (1981)Google Scholar
  15. 15.
    Penrose, R.: The Emperor’s New Mind: Concerning Computers Minds and the Laws of Physics. OUP, Oxford (1989)Google Scholar
  16. 16.
    Pollock, J.L.: What Am I? Virtual machines and the mind/body problem. Philosophy and Phenomenological Research 76(2), 237–309 (2008), CrossRefGoogle Scholar
  17. 17.
    Rochat, P.: The Infant’s World. Harvard University Press, Cambridge (2001)Google Scholar
  18. 18.
    Romanes, G.J.: Mental evolution in animals, K. Paul, Trench, London (1883),
  19. 19.
    Ryle, G.: The Concept of Mind. Hutchinson, London (1949)Google Scholar
  20. 20.
    Ryser, P.: Creative Choice: How the Mind Could Causally Affect the Brain. Journal of Consciousness Studies 16(2-3), 6–29 (2009)Google Scholar
  21. 21.
    Shanahan, M.P.: Consciousness, Emotion, & Imagination: A Brain-Inspired Architecture for Cognitive Robotics. In: AISB 2005 Symp. on Next Generation Approaches to Machine Consciousness, pp. 26–35 (2005)Google Scholar
  22. 22.
    Sloman, A.: The Computer Revolution in Philosophy. Harvester Press, Hassocks (1978), Google Scholar
  23. 23.
    Sloman, A.: What Cognitive Scientists Need to Know about Virtual Machines. In: Taatgen, N.A., van Rijn, H. (eds.) Proc. 31st Ann. Conf. of the Cognitive Science Society, pp. 1210–1215. Cognitive Science Society, Austin (2009), Google Scholar
  24. 24.
    Sloman, A.: Why the “hard” problem of consciousness is easy and the “easy” problem hard (And how to make progress) (2009),
  25. 25.
    Sloman, A.: An Alternative to Working on Machine Consciousness. Int. J. Machine Consciousness (2010),
  26. 26.
    Sloman, A.: Phenomenal and Access Consciousness and the “Hard” Problem: A View from the Designer Stance. Int. J. of Machine Consciousness (2010),
  27. 27.
    Whittaker, T.: Review of G.J.Romanes Mental evolution in animals. Mind 9(34), 291–295 (1884), CrossRefGoogle Scholar
  28. 28.
    Wiener, N.: Cybernetics: or Control and Communication in the Animal and the Machine, 2nd edn. The MIT Press, Cambridge (1961)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Aaron Sloman
    • 1
  1. 1.School of Computer ScienceUniversity of BirminghamUK

Personalised recommendations