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Towards making computers conscious: trends and challenges

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The question of consciousness has puzzledmany great philosophersfrom time immemorial and rightly so because of the fact that our brain is made up of flesh and blood and yet produces such vivid subjective experience s of reality. The topic of consciousness has been confined to the field of philosophy till recently; later, neuroscientists, psychologists and computer scientists have joined this quest to resolve the enigma of consciousness. Amongst many such varying approaches to understanding consciousness, there is a particular perspective called “Machine Consciousness” embraced by many prominent scientists and engineers working on reproducing consciousness in a machine. This paper is an exhaustive review of the advancements in machine consciousness and the underlying theories and cognitive architectures. This paper also covers criticisms and shortfalls of relevant approaches and elaborates on machine consciousness’s relationship with other fields.

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References

  1. Meacham Bill, Don’t say” Consciousness”: toward a uniform vocabulary of subjectivity, sociology and anthropology. 4 (12) :1099–1107, (2016).

  2. Gomez, D.: Progress in machine consciousness. Conscious. Cogn.Cogn. 17, 887–910 (2008)

    Article  Google Scholar 

  3. Reggia, J.: The rise of machine consciousness. Neural Netw.Netw. 44, 112–131 (2013)

    Article  Google Scholar 

  4. John, S.: Chinese room argument. Scholarpedia 4(8), 3100 (2009)

    Article  Google Scholar 

  5. Block N, O Flanagan, and G. Guzeldere (Eds.), The nature of consciousness philosophical debates, Cambridge, Mass., MIT Press, (1997) (Chapter17)

  6. Dennett Daniel C, Consciousness explained, Little Brown and Company (1991).

  7. Yampolskiy Roman V, Artificial consciousness: An illusionary solution to the hard problem, Reti, Saperi, Linguaggi, Societa Editrice Il Muline,287–318 (2018).

  8. David Chalmers, The consciousness mind, Oxford University Press (1996).

  9. Signorelli Camilo Migvel: can computers become conscious and overcome humans? Frontiers in Robotics and AI. Published Online (2018). https://doi.org/10.3389/frobit.2018.00121

    Article  Google Scholar 

  10. Kawato Mitsuo, from ‘understanding the brain by creating the brain’ towards manipulative neuroscience, Philosophical Transactions of the Royal Society B, Biological Sciences, (363)1500:2201–14(2008).

  11. McGilchrist, Ian, the master and his emissary: The divided brain and the making of the western world, Yale University Press (2009).

  12. Huxley T H, On the hypothesis that animals are automata and its history, Nature (10)362–366 (1874).

  13. Norvig, P.: Stuart J Russell, Artificial intelligence: A modern approach, Englewood Cliffs. Prentice Hall, NJ (1994)

    Google Scholar 

  14. Christof, K., Mashimini, M., Boly, M., Tononi, G.: Neural correlates of consciousness: progress and problems. Nat. Rev. Neurosci.Neurosci. 17, 307–321 (2016)

    Article  Google Scholar 

  15. Crick Francis, Christof Koch, A framework for consciousness, Nature Neuroscience (6)2:119–26, (2003).

  16. Parton, A.: P Malhotra. M Hussain, Hemispatial neglect, Journal of Neurology, Neurosurgery and Psychiatry 75(1), 13–21 (2004)

    Google Scholar 

  17. Tononi G, G M Edelman, O Sporns, Complexity and coherency: Integrating information in the brain, Trends in Cognitive Science (2)12:474–484(1998).

  18. Cutting J, Study of anosognosia, Journal of Neurology Neurosurgery and Psychiatry (41)6:548–556 (1978).

  19. Gordon G Gallup Jr, James R Anderson, Daniel J Shillito, The mirror test, The Cognitive Animal: Empirical and Theoretical Perspectives on Animal Cognition,325–333, MIT Press, Cambridge, MA (2002).

  20. McLeod S. A Maslow's hierarchy of needs. retrieved from https://www.simplypsychology.org/maslow.html, (2018).

  21. Yang Qin, Ramviyas Parasuraman, Hierarchical needs based self-adaptive framework for cooperative multi-robot system, IEEE International Conference on Systems. Man, and Cybernetics (SMC), 2991–2998(2020),

  22. Baars, B.: In the theatre of consciousness. Oxford University Press, New York, NY (1997)

    Book  Google Scholar 

  23. Dehaene, S.: C Sergent and Jean-Pierre Chengeux, A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proceedings of National Academy of Sciences 100(14), 8520–8525 (2003)

    Article  Google Scholar 

  24. Mashour George A, Peter Roelfsema Jean-Pierre Changeux, Stanislas Dehaene, Conscious processing and the global neuronal workspace hypothesis, Neuron (105)5:.776–798(2020).

  25. Tononi G, Consciousness as integrated information, Biological Bulletin (215) 216–242(2008).

  26. Mayner W G P, William Marshall, Larissa Albantakis, Graham Findlay, Robert Marchman, Giulio Tononi, PyPhi: A toolbox for integrated information theory, PLOS Computational Biology, (14)7: e1006343:1–21 (2018).

  27. Guevara Erra, R., Mateos, D.M., Wennberg, R., Perez Velazquez, J.L.: Statistical mechanics of consciousness: maximization of information content of network is associated with conscious awareness. Phys. Rev. E 94(5–1), 52402 (2016)

    Article  Google Scholar 

  28. Guevara Ramon, Diego M Mateas, Jose Luis Perez Velazquez, Consciousness as an emergent phenomenon: A tale of different levels of description, Entropy, (2) 9:921, https://doi.org/10.3390/e22090921(2020).

  29. Mason, J.W.D.: from learning to consciousness: an example using expected float entropy minimisation. Entropy 21(60), 1–19 (2019)

    Google Scholar 

  30. Thomas Parr, Giovanni Pezzulo and Karl J Friston Active inference: the free energy principle in mind, brain and behavior, MIT Press (2022).

  31. Friston Karl, James Kilner, Lee Harrison, A free energy principle for the brain, Journal of Physiology-Paris, 70–87 (2006).

  32. Michael, K., Parr, T., Palacios, E., Friston, K., Kiverstein, J.: The Markov blankets of life: autonomy, active inference and the free energy principle. Journal of Royal Society Interface 15(20170792), 1–11 (2018). https://doi.org/10.1098/rsif.2017.0792

    Article  Google Scholar 

  33. Schmidhuber J. Driven by compression progress: A simple principle explains essential aspects of subjective beauty, novelty, surprise, interestingness, attention, curiosity, creativity, art, science, music, jokes. In: Pezzulo G., Butz M.V., Sigaud O., Baldassarre G. (Eds.) Anticipatory Behavior in Adaptive Learning Systems. ABiALS 2008. Lecture Notes in Computer Science, vol 5499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02565-5_4, (2009).

  34. Ron, S.: Desiderata for cognition architectures. Philos. Psychol. 17(3), 341–373 (2004)

    Article  Google Scholar 

  35. Newell, A, SOAR as a unified theory of cognition: issues and explanations, behavioral and brain sciences (15): 464–492, doi: https://doi.org/10.1017/S0140525X00069740 (1992).

  36. Arrabales Raul, Agapito Ledezma and Araceli Sanchis, ConsScale A pragmatic scale for measuring the level of consciousness in artificial agents, Journal of Consciousness Studies (17,3–4) :131–64 (2010).

  37. Gardener Howard, The mind’s new science: A history of the cognitive revolution, Basic Books, (1985).

  38. Gamez, D.: Empirically grounded claims about consciousness in computers. International journal of machine consciousness 4, 421–438 (2012)

    Article  Google Scholar 

  39. Thorisson K, H. Helgasson, Cognitive architectures and autonomy: a comparative review, Journal of Artificial General Intelligence (3) 2:.1–30 (2012).

  40. Samosonovich Alex, V.: toward a cognitive unified catalog of implemented cognitive architectures. Biologically Inspired Cognitive Architectures 221, 195–244 (2010)

    Google Scholar 

  41. Luliia, K.: John K Tsotsos, 40 years of cognitive architecture: core cognitive abilities and practical applications. Artif. Intell. Rev.. Intell. Rev. 53, 17–94 (2020)

    Article  Google Scholar 

  42. Rotenberg Vadim, S.: Moravec’s Paradox: Consideration in the context of two brain hemisphere functions. Act. Nerv. Super.Nerv. Super. 55(3), 108–111 (2013)

    Article  Google Scholar 

  43. David, H., Goertzel, B.: OpenCog: a software framework for integrative artificial general intelligence. Frontiers Artificial Intelligence Appl. 171(1), 468–472 (2008)

    Google Scholar 

  44. Stan, F., Madl, T., D’Mello, S., Snaider, J.: LIDA: a systems-level architecture for cognition, emotion and learning. IEEE Trans. Auton. Ment. Dev. 6(1), 19–41 (2014)

    Article  Google Scholar 

  45. Rohrer B, BECCA: Reintegrating AI for natural world interaction, In AAAI Spring Symposium, Designing Intelligent Robots: Reintegrating AI, AAAI Technical Report SS-12–02 (2012).

  46. Eliasmith C, How to Build a Brain: A neural architecture for biological cognition, Oxford University Press (2013).

  47. Eidenberger Robert, Raoul Zollner and Josef Scharinger, An integrated action perception module for a distributed cognitive architecture, IEEE Explore (2009).

  48. Mills, J. A. Hull's theory of learning as a philosophical system: I. An outline of the theory, Canadian Psychological Review /Psychologie Canadienne, (19)1: 27– 40 (1978). https://doi.org/10.1037/h0081460.

  49. Kenrick, D.T., Neuberg, S.L., Griskevicius, V., Becker, D.V., Schaller, M.: Goal-driven cognition and functional behavior: the fundamental-motives framework. Curr. Dir. Psychol. Sci.. Dir. Psychol. Sci. 19(1), 63–67 (2010)

    Article  Google Scholar 

  50. Gudwin, R.R.: A review of motivational systems and emotions in cognitive architectures and systems. Artificial Intelligence, Lecture Notes in Computer Science 11866, 65–84 (2019)

    Google Scholar 

  51. Cyntha L Breazeal, Sociable machines: expressive social exchange between humans and robots, PhD Thesis, Massachusetts Institute of Technology (2000).

  52. Hudlicka, E Reasons for emotions: modeling emotions in integrated cognitive systems, In W. D. Gray (Ed.), Integrated Models of Cognitive Systems, 263–278, Oxford University Press (2007).

  53. Marinier III Robert, John Laird, Toward a comprehensive computational model of emotions and feelings, Sixth International Conference on Cognitive Modeling, 172–177 (2004).

  54. Jordi, V., Talanov, M., Distefano, S., Lazzara, M., Tchitchigin, A., Nurgaliev, L.: A cognitive architecture for the implementation of emotions in computing systems. Biologically Inspired Cognitive Architectures 15, 34–40 (2016)

    Article  Google Scholar 

  55. Carbonell, J., Etzioni, O., Gil, Y., Joseph, R., Knoblock, C., Minton, S., Veloso, M.: Prodigy: an integrated architecture for planning and learning. SIGART Bull. 2(4), 51–55 (1991)

    Article  Google Scholar 

  56. Goertzel B, C Pennachin, The Novamente Artificial intelligence engine, artificial General Intelligence :63–129 (2007).

  57. Eliasmith, C.; Stewart, T.C.; Choo, X.; Bekolay, T.; DeWolf, T.; Tang, Y.; Rasmussen, D, A large-scale model of the functioning brain, Science, 338 (6111): 1202–5. doi:https://doi.org/10.1126/science.1225266 (2012)

  58. Ramamurthy Uma, Bernard J. Baars, Sidney K. D' Mello, and Stan Franklin, LIDA: A working model of cognition, Proceedings of the 7th International Conference on Cognitive Modeling (Eds: Danilo Fum, Fabio Del Missier and Andrea Stocco) 244–249 (2006).

  59. Laird John, E.: Allen Newell, Paul S Rosenbloom, Soar: an architecture for general intelligence. Artif. Intell.. Intell. 33(1), 1–64 (1987)

    Article  Google Scholar 

  60. Ferrigno S, Huang Yiyun, Jessica F Cantlon, Reasoning through the disjunctive syllogism in monkeys, Psychological Science: 61–9 (2021).

  61. Bengio Y, The consciousness prior, ar**v; 1709.08568v2 [cs. LG] (2019).

  62. Aleksander, I., Dunmall, B, Axioms and tests for the presence of minimal consciousness in agents. In Machine Consciousness, O. Holland, (ed)., Imprint Acad, (2003).

  63. Dietrich Arne, Functional neuroanatomy of altered states of consciousness: The transient hypofrontality hypothesis, Consciousness and cognition,12:231–256 www.elsevier.com/locate/concog (2003).

  64. Wiedermann Jiri, Jan van Leeuwen. Finite state machines with feedback: an architecture supporting minimal machine consciousness, LNCS 11558, F. Manea et al. (Eds.): CiE 2019 :286–297(2019).

  65. Flavell, J.H.: Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry. Am. Psychol. 34(10), 906–991 (1979)

    Article  Google Scholar 

  66. Stevan, H.: The symbol grounding problem. Physica D D 42(1–3), 335–346 (1990)

    Google Scholar 

  67. Josh, B., Zykov, V., Lipson, H.: Resilient machines through continuous self-modeling. Science 314, 1118–1121 (2006)

    Article  Google Scholar 

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Acknowledgements

The author would like to thank the National Academy of Sciences India (NASI) for support during this work. The anonymous Reviewer is acknowledged for several useful suggestions which improved the quality of presentation. The Editor Dr. Nasser Lotfi’s specific technical suggestions have been very constructive.

Funding

The author receives a nominal Honorarium of Rs. 30,000 per month (USD 400Appx) which is taxable at 33%; this support is received from the National Academy of Sciences India (NASI), a non-profit making Academy, which is the counterpart of National Academy of Science, USA. This support has been acknowledged in the Acknowledgements. There is no commercial financial funding.

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Patnaik, L.M. Towards making computers conscious: trends and challenges. Iran J Comput Sci 7, 139–153 (2024). https://doi.org/10.1007/s42044-023-00164-7

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