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A systematic review of integrated information theory: a perspective from artificial intelligence and the cognitive sciences

Guerrero, Luz Enith, Castillo, Luis Fernando, Arango-López, Jeferson, Moreira, Fernando·2025·Neural Computing and Applications
DOI 10.1007/s00521-023-08328-z
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  1. Patnaik LM, Kallimani JS (2017) Promises and limitations of conscious machines. In: Menon S, Nagaraj N, Binoy VV (eds) Self, culture and consciousness: interdisciplinary convergences on knowing and being. Springer Singapore, Singapore
  2. Crick F (1995) Astonishing hypothesis: the scientific search for the soul, new york, scribner reprint edition · DOI
  3. Penrose R (1996) Shadows of the mind: a search for the missing science of consciousness United States of America. Oxford University Press, Oxford · DOI
  4. Chalmers DJ (1995) Facing up to the problem of consciousness. J Conscious Stud 2:19
  5. Nilsson NJ (2009) The quest for artificial intelligence. Cambridge University Press · DOI
  6. Holland O, Gamez D (2009) Artificial intelligence and consciousness. In: Banks WP (ed) Encyclopedia of consciousness. Academic Press
  7. Stephan KD, Klima G (2021) Artificial intelligence and its natural limits. AI Soc 36:9–18 · DOI
  8. Nazri A, Ghani AAA, Hafez I, Ng KY (2018) A new theoretical framework for testing consciousness in a machine. In: International conference on soft computing and data mining. Springer, pp 330–339 · DOI
  9. Kriegeskorte N, Douglas PK (2018) Cognitive computational neuroscience. Nat Neurosci 21:1148–1160 · DOI · Paper page
  10. Schwartz EL (1990) Computational neuroscience. MIT press
  11. Makin JG, Moses DA, Chang EF (2020) Machine translation of cortical activity to text with an encoder–decoder framework. Nat Neurosci 23(4): 575–582 · DOI · Paper page
  12. Wendin G (2019) Can biological quantum networks solve np-hard problems? Adv Quantum Technol 2(7–8):1800081 · DOI
  13. Russell S, Norvig P (2020) Artificial intelligence: a modern approach, Hoboken · DOI
  14. Liao Y, Yan M, Tang S (2021, March). The robot consciousness based on empirical knowledge. In Journal of Physics: Conference Series (Vol. 1861, No. 1, p. 012103). IOP Publishing · DOI
  15. Buczak AL, Guven E (2015) A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Commun Surv Tutor 18(2):1153–1176 · DOI · Paper page
  16. Tozzi A (2019) The multidimensional brain. Phys Life Rev 31:86–103 · DOI
  17. Gauvrit N, Zenil H, Tegnér J (2017) The information-theoretic and algorithmic approach to human, animal, and artificial cognition. Representation and reality in humans, other living organisms and intelligent machines 117–139 · DOI
  18. Kralik J, Lee JH, Rosenbloom PS, Jackson PC, Epstein SL, Romero OJ, Sanz R, Larue O, Schmidtke HR, Lee SW, Mcgreggor K (2018) Metacognition for a common model of cognition. Proc Comput Sci 145:730–739 · DOI
  19. Chandra R (2017) Towards an affective computational model for machine consciousness. In: Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14–18, 2017, Proceedings, Part V 24 (pp. 897–907). Springer International Publishing · DOI
  20. Block N (2009) Comparing the major theories of consciousness. In: The cognitive neurosciences, 4th edn. Massachusetts Institute of Technology, Cambridge. · DOI
  21. Manzotti R (2019) A physicalist causally oriented foundation for a conscious machine based on the spread mind. In: AAAI spring symposium: towards conscious AI systems
  22. Koch C, Tononi G (2008) Can machines be conscious? IEEE Spectr 45:55–59 · DOI
  23. Tononi G, Koch C (2015) Consciousness: here, there and everywhere? Philos Trans R Soc Lond Ser B Biol Sci 370(1668):20140167 · DOI · Paper page
  24. Tononi G, Boly M, Massimini M, Koch C (2016) Integrated information theory: from consciousness to its physical substrate. Nat Rev Neurosci 17:450–461 · DOI · Paper page
  25. Paz F, Pow S (2016) A systematic mapping review of usability evaluation methods for software development process. Int J Softw Eng I Appl 10(1):165–178
  26. Petersen K, Feldt R, Mujtaba S, Mattsson M (2008) Systematic mapping studies in software engineering. In: Proceedings of the 12th international conference on evaluation and assessment in software engineering, vol 17 · DOI · Paper page
  27. Petersen K, Vakkalanka S, Kuzniarz L (2015) Guidelines for conducting systematic mapping studies in software engineering: an update. Inform Softw Technol 64:18 · DOI · Paper page
  28. Kitchenham B, Brereton P (2013) A systematic review of systematic review process research in software engineering. Inf Softw Technol 55(12): 2049–2075 · DOI · Paper page
  29. Franco-bedoya O, Ameller D, Costal D, Franch X (2017) Open source software ecosystems: a systematic mapping. Inform Softw Technol 91:160–185 · DOI
  30. Manikas, k. (2016) Revisiting software ecosystems research: a longitudinal literature study. J Syst Softw 117:84–103 · DOI
  31. Kitchenham B, Pearl Brereton O, Budgen D, Turner M, Bailey J, Linkman S (2009) Systematic literature reviews in software engineering – a systematic literature review. Inform Softw Technol 51:7–15 · DOI · Paper page
  32. Miles MB, Huberman AM, Saldana J (2019) Qualitative data analysis: a methods sourcebook. Sage Publications
  33. Kitchenham B, Brereton P (2013) A systematic review of systematic review process research in software engineering. Inf Softw Technol 55:2049–2075 · DOI · Paper page
  34. McGreggor K (2020). An experience is a knowledge representation. Common Model of Cognition Bulletin 1(2): 420–424
  35. Antonopoulos C, Fokas A, Bountis T (2015) Dynamical complexity in the c.elegans neural network. Eur Phys J Spec Top 225:1255–1269 · DOI
  36. Moreno RA., de Miguel AS, Espino AL (2011). Evaluation and development of consciousness in artificial cognitive systems. Ph. D. dissertation
  37. Montes GA (2017) Non-ordinary consciousness for artificial intelligence. Springer International Publishing, pp 348–362 · DOI
  38. Friedman DA., Søvik E (2021) The ant colony as a test for scientific theories of consciousness. Synthese 198(2), 1457–1480 · DOI
  39. Reggia J, Monner D, Sylvester J (2014) The computational explanatory gap. J Conscious Stud 21(9–10):153–178
  40. Banerjee R, Pal SK (2015) Z*-numbers: augmented z-numbers for machine-subjectivity representation. Inf Sci 323:143–217 · DOI
  41. Niizato T, Sakamoto K, Mototake YI, Murakami H, Tomaru T, Hoshika T, Fukushima T (2020) Finding continuity and discontinuity in fish schools via integrated information theory. PLoS ONE 15(2):e0229573 · DOI
  42. Marcolli M (2021) Topological model of neural information networks. Springer International Publishing, 623–633 · DOI
  43. Javarone MA, Gosseries O, Marinazzo D, Noirhomme Q, Bonhomme V, Laureys S, Chennu S (2020) A mean field approach to model levels of consciousness from eeg recordings. J Stat Mech Theory Exp 2020(8):083405 · DOI
  44. Reggia J (2013) The rise of machine consciousness: studying consciousness with computational models. Neural Netw Off J Int Neural Netw Soc 44:112–131 · DOI
  45. Iklé M, Goertzel B, Bayetta M, Sellman G, Cover C, Allgeier J, Smith R, Sowards M, Schuldberg D, Leung M, Belayneh A, Smith G, Hanson D (2019) Using tononi phi to measure consciousness of a cognitive system while reading and conversing [online]. https://ceur-ws.org/Vol-2287/paper20.pdf Accessed 2020
  46. Popiel NJM, Khajehabdollahi S, Abeyasinghe PM, Riganello F, Nichols ES, Owen AM, Soddu A (2020) The emergence of integrated information, complexity, and ‘consciousness’ at criticality. Entropy 22:339 · DOI
  47. Farnsworth KD (2018) How oganisms gained causal independence and how it might be quantified. Biology 7:38 · DOI
  48. Kalita P, Langa JA, Soler-Toscano F (2019) Informational structures and informational fields as a prototype for the description of postulates of the integrated information theory. Entropy 21:493 · DOI
  49. Dodig-Crnkovic G, Von Haugwitz R (2017) Reality construction in cognitive agents through processes of info-computation. In: Dodig-Crnkovic G, Giovagnoli R (eds) Representation and reality in humans, other living organisms and intelligent machines. Springer International Publishing, Cham · DOI
  50. Reggia JA, Katz G, Huang DW (2016) What are the computational correlates of consciousness? Biol Inspir Cognit Arch 17:101–113
  51. Arrabales R, Ledezma A, Sanchis A (2009) Strategies for measuring machine consciousness. Int J Mach Conscious 01:193–201 · DOI
  52. Aguilera M, Di Paolo EA (2021) Critical integration in neural and cognitive systems: beyond power-law scaling as the hallmark of soft assembly. Neurosci Biobehav Rev 123:230–237 · DOI
  53. Hunt T (2020) Calculating the boundaries of consciousness in general resonance theory. J Conscious Stud 27:55–80
  54. Langer C, Ay N (2021) How morphological computation shapes integrated information in embodied agents. Frontiers in Psychol. 5385 · DOI
  55. Schneider S (2020) How to catch an ai zombie: testing for consciousness in machines. Ethics of artificial intelligence · DOI
  56. Arrabales R, Ledezma A, Sanchis A (2010) ConsScale: A pragmatic scale for measuring the level of consciousness in artificial agents. J Consciousness Stud 17(3-4), 131–164
  57. Pizzi R, Musumeci M (2017) Coding Mental States from EEG Signals and evaluating their Integreted Information Content: a Computational Intelligence Approach. Int J Circ Syst Signals Process 11(4464):464–470
  58. Nilsen AS, Juel B, Marshall W (2019) Evaluating approximations and heuristic measures of integrated information. Entropy 21:525 · DOI
  59. Elamrani A, Yampolskiy RV (2019) Reviewing tests for machine consciousness. J Conscious Stud 26:35–64
  60. Kanade VA (2020) A hybrid evolutionary algorithm for evolving a conscious machine. In Intelligent Systems Design and Applications: 18th International Conference on Intelligent Systems Design and Applications (ISDA 2018) held in Vellore, India, December 6-8, 2018, Volume 2 (pp. 1045–1054). Springer International Publishing · DOI
  61. Kitazono J, Kanai R, Oizumi M (2020) Efficient search for informational cores in complex systems: application to brain networks. Neural Netw 132:232–244 · DOI
  62. Virmani M, Nagaraj N (2019) A novel perturbation based compression complexity measure for networks. Heliyon 5:e01181 · DOI
  63. Barghout L (2018) Hypernym and spatial-taxon hierarchy. A cognitive informatics and fuzzy logic approach to combining linguistic and image taxonomies. In: 2018 IEEE 17th international conference on cognitive informatics and cognitive computing (ICCI* CC), pp 575–582. IEEE · DOI
  64. Van Hateren JH (2019) A theory of consciousness: computation, algorithm, and neurobiological realization. Biol Cybern 113:357–372 · DOI
  65. Shanahan M (2015) Ascribing consciousness to artificial intelligence. arXiv preprint arXiv:1504.05696 · arXiv
  66. Findlay G, Marshall W, Albantakis L, Mayner W, Koch C, Tononi G (2019). Dissociating intelligence from consciousness in artificial systems–Implications of Integrated Information Theory. In Proceedings of the 2019 Towards Conscious AI Systems Symposium, AAAI SSS19
  67. Bedia M, Castillo L (2016) Hacia una teoría de la mente corporizada: la influencia de los mecanismos sensomotores en el desarrollo de la cognición. Ánfora 17:101–124 · DOI
  68. Montemayor C, de Barros JA, de Assis lPG, (2019) Implementation, formalization, and representation: challenges for integrated information theory. J Conscious Stud 26:107–132
  69. Bach J (2019) The cortical conductor theory: Towards addressing consciousness in ai models. In Biologically Inspired Cognitive Architectures 2018: Proceedings of the Ninth Annual Meeting of the BICA Society (pp. 16–26). Springer International Publishing · DOI
  70. Kelley D (2018) The independent core observer model computational theory of consciousness and the mathematical model for subjective experience. In: 2018 4th annual international conference on network and information systems for computers (ICNISC), 19–21 April 2018, pp 396–400 · DOI
  71. List C (2018) What is it like to be a group agent? Noûs 52:295–319 · DOI
  72. Schneider S, Velmans M (2017) The Blackwell Companion to Consciousness. Blackwell Publishing, 175–179 · DOI
  73. Thagard P, Stewart TC (2014) Two theories of consciousness: semantic pointer competition versus Information integration. Conscious Cognit 30:73–90 · DOI
  74. Calvo P, Baluška F, Trewavas A (2021) Integrated information as a possible basis for plant consciousness. Biochem Biophys Res Commun 564:158–165 · DOI
  75. Baudot P (2019) Elements of qualitative cognition: an information topology perspective. Phys Life Rev 31:263–275 · DOI
  76. Mallatt J (2021) A traditional scientific perspective on the integrated information theory of consciousness. Entropy 23(6):650 · DOI
  77. Barthelmeß U, Furbach U, Schon C (2020) Consciousness and Automated Reasoning. arXiv preprint https://doi.org/10.48550/arXiv.2001.09442 · DOI
  78. Albantakis L, Massari F, Beheler-Amass M, Tononi G (2021) A macro agent and its actions. In Top-Down Causation and Emergence (pp. 135–155). Cham: Springer International Publishing
  79. Gamez D (2010) Information integration based predictions about the conscious states of a spiking neural network. Conscious Cogn 19:294–310 · DOI
  80. Sylvester JC, Reggia JA, Weems SA, Bunting MF (2013) Controlling working memory with learned instructions. Neural Netw 41:23–38 · DOI
  81. Aleksander I, Gamez D (2009) Iconic training and effective information: evaluating meaning in discrete neural networks. AAAI fall symposium - technical report
  82. Marshall W, Gomez-ramirez J, Tononi G (2016) Integrated information and state differentiation. Front Psychol 7:926 · DOI · Paper page
  83. Oizumi, m., tsuchiya, n. & amari, s. I. (2016) Unified framework for information integration based on information geometry. Proc Natl Acad Sci 113:14817–14822 · DOI
  84. Krohn, S., Ostwald, D. (2017). Computing integrated information. Neuroscience of consciousness, 3(1): 1-16. · DOI
  85. Aguilera M, di Paolo AE (2019) Integrated information in the thermodynamic limit. Neural netw 114:136–146 · DOI
  86. Tajima S, Kanai R (2017) Integrated information and dimensionality in continuous attractor dynamics. Neurosci Conscious 2017(1):nix011 · DOI
  87. Bach J (2019) The cortical conductor theory: towards addressing consciousness in AI models. In: Biologically inspired cognitive architectures 2018 · DOI
  88. Aguilera, M. (2019). Scaling behaviour and critical phase transitions in integrated information theory. Entropy 21(12):1198. https://doi.org/10.3390/e21121198 · DOI
  89. Barrett A, Seth AK (2011) Practical measures of integrated information for time-series data. PLoS Comput Biol 7:e1001052 · DOI · Paper page

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Metadata

Authors
Guerrero, L. E., Castillo, L. F., Arango-López, J., & Moreira, F.
ORCID
Venue
Neural Computing and Applications
Publisher
Springer Science and Business Media LLC
Published
2023-02-07
Volume
37
Issue
11
Pages
7575-7607
ISSN
  • 0941-0643
  • 1433-3058
DOI
10.1007/s00521-023-08328-z
Cited by
11
References
16
Language
en
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