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Future Directions of Modelling the Uncertainty in the Cognitive Domain

  • Sisir RoyEmail author
Chapter

Abstract

Recent experimental findings clearly suggest that classical probability theory is still not successful to explain modalities in human cognition, especially in connection to decision making. The major problem seems to be the presence of epistemic uncertainty and its effects on cognition at any time point. Moreover, the stochasticity in the model arises due to the unknown path or trajectory (the definite state of mind at each point in time) a person follows. In fact, there exists more ambiguity than clarity in some aspects of cognition, for example, regarding cognitive affective decision-making behavior and subsequent choices (George et al. in Academy of Management Review 31: 347–365, 2006). The concept of ambiguity, its typical role and its function are not only long-standing debatable concerns in the humanities but also assume a similar level of importance, and are the subject of much debate, in contemporary neurological and cognitive approaches. For example, biologist Fredrick Grinnell made an argument clarifying that ambiguity “is inherent in carrying out and reporting research” (Grinnell in Science and Engineering Ethics 5:205, 1999). Not only that, but he also pointed out some parameters of ambiguity that support his view, for instance, the difficulty of distinguishing between data and noise in research “at the edge of discovery” (ibid. 207). Interestingly, as a positive side of ambiguity, he observed “while ambiguity in method and procedure—as an aspect of data and its interpretation—is clearly a potential problem, posing the risk of distortion, it is also associated here with creative insight.” The consideration of “black box model of human mental functions” produces much ambiguity. So, as we are aware of the intertwined mathematical, neurological and cognitive mysteries of the brain, ultimately, these very characteristics are challenges faced by the human cognition and give rise to a very complicated and complex integrative system of cognitive computation and affective perception. A generalized version of probability theory, borrowing the idea from the quantum paradigm, may be a plausible approach. Quantum theory enables a person to be in an indefinite state (superposition state) in the context of neurobiology, especially in relation to central nervous system (CNS), and this allows all these states to be potentially (of course, with proper probability amplitudes) expressible at each moment. Thus, a superposition state seems to provide a better representation of the conflict, ambiguity or uncertainty that a person experiences at each moment. This situation can be described in somewhat poetic language, i.e., the dynamical laws, as demonstrated by nature, allow equations but are only sometimes posed by the Mind of the experimentalist. This way, consciousness (as expressed in his introduction to consciousness or cognition can be expressed as only a critical description of human activity and not as a theory of mind. Some critical remarks about handling the ambiguity and contradictions due to emotions within quantum probability framework are made in this chapter. Mental states and related decision making have been widely discussed in various ancient and medieval Indian traditions. The existence of an indefinite state of mind was discussed by many Indian philosophical schools, including Buddhism. The concept of the neutral mind, as well as equanimity, is discussed in this chapter, especially because it has a potential to be related to modern neuroscience, as well as to quantum theory.

Keywords

Affective computing Quantum probability Indefinite state of mind Neutral mind Equanimity Buddhist school Samatvam 

References

  1. Anuruddha, B. & Bodhi, B. (2000) A comprehensive manual of Abhidhamma: the Abhidhammattha sangaha of Ācariya Anuruddha (1st BPS Pariyatti ed.); Seattle.Google Scholar
  2. Busemeyer, J.R., Pothos, E.M., Franco, R., & Trueblood, J. S. (2011); Psychol. Rev., 118 (2), 193-218Google Scholar
  3. Conte, Elio et. al. (2009a); Open system and Information dynamics, 16, 85.Google Scholar
  4. Conte E., Khrennikov, Y., Toderello, O. et al.; (2009b); Open system & Information Dynamics, 16(1),1-17.Google Scholar
  5. Damasio Antonio (2010); Neural basis of emotions; Scholarpedia; 6(3);1804.Google Scholar
  6. Etkins Amit, Buchel C. & Gross, J.J. (2015); Nature Reviews Neuroscience, 16, 693-700 (published on line 20 October 2015).Google Scholar
  7. George E., Chattopadhyay P., Barden J. (2006) Academy of Management Review 31, 347-365.Google Scholar
  8. Grinnell, F. (1999) Science and Engineering Ethics, 5: 205–214.Google Scholar
  9. Heisenberg (1958) Physics and Philosophy; New York, Harper.Google Scholar
  10. Kāśyapa Jagadīśa Bhikku (1982) (ed.) The Abhidhamma Philosophy, or, the Psycho-Ethical Philosophy of Early Buddhism; Bharatiya Vidya Prakashan.Google Scholar
  11. Max Planck (1936) Philosophy of physics, W.W. Norton & Company, inc., p. 46Google Scholar
  12. McCollum, Gin (2002) Systems of Logical systems; “Neuroscience and quantum logic: Foundation of science, Springer.Google Scholar
  13. Patanjali, Vacaspati Misra, Vyasa, and James Haughton Woods (1914); The Yoga-System of---or the ancient Hindu Doctrine of concentration of mind embracing the mnemonic rules, called Yoga-Sutras, of---and the comment, called Yoga-Bhashya (etc.); Harvard University Press.Google Scholar
  14. Priest, G. (2002) Paraconsistent Logic; Handbook of Philosophical Logic (2nd edition);vol 6; gabby & F. Guenthner (eds); Dordrecht: Kluwer Academic Publishers; pp 287-393.Google Scholar
  15. Schrödinger, Erwin (1935) Die gegenwärtige Situation in der Quantenmechanik (The present situation in quantum mechanics). Naturwissenschaften; 23 (49): 807–812.Google Scholar
  16. Shimony Abner (1993); “The Family of Propensity Interpretations of Probability,” Lecture at University of Bologna, 1988 Box 1, Folder 19 Abner Shimony Papers, 1947-2009, ASP.2009.02, Archives of Scientific Philosophy, Special Collections Department, University of Pittsburgh.Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.National Institute of Advanced Studies, IISc CampusBengaluruIndia

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