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Toward a Comprehensive List of Necessary Abilities for Human Intelligence, Part 1: Constructing Knowledge

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Artificial General Intelligence (AGI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13539))

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Abstract

In [1], Adams et al. chart a roadmap toward the grand AI vision, with human-level (or greater) intelligence as destination. To that end, in this and a companion paper [2], I take one of the next steps they outline, to “refine the list of specific competency areas” in human cognition. It is argued that we should move toward a comprehensive list of all required abilities to make clearer what is known, unknown, and what the next steps should be, such as resolving how abilities piece together into the larger-scale puzzle of general intelligence. This paper concentrates roughly on the first half of cognitive processing, from initial input to knowledge construction and memory storage (including, for example, emotion, perception, attention, memory, and knowledge construction processes, such as reasoning, imagination, and simulation); with the second paper on the action-based second half that uses the knowledge for constructive outcomes.

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References

  1. Adams, S.S., et al.: Mapping the landscape of human-level artificial general intelligence. AI Magazine 33(1), 25–41 (2012)

    Article  Google Scholar 

  2. Kralik, J.D.: Toward a comprehensive list of necessary abilities for human intelligence, Part 2: Using Knowledge. In: Proc. 15th Conf. on Artificial General Intelligence (2022)

    Google Scholar 

  3. Goertzel, B.: Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence 5(1), 1–46 (2014)

    Article  Google Scholar 

  4. Laird, J.E., Lebiere, C., Rosenbloom, P.S.: A Standard Model of the Mind. AI Magazine 38(4), 13–26 (2017)

    Article  Google Scholar 

  5. Reisberg, D.: Cognition. WW Norton & Co., New York (2021)

    Google Scholar 

  6. Holyoak, K.J., Morrison, R.G. (eds.) Oxford Handbook of Thinking and Reasoning. Oxford University Press (2012)

    Google Scholar 

  7. Goswami, U.: Cognitive development. Routledge, London (2008)

    Google Scholar 

  8. Mazur, J.E.: Learning and Behavior. Routledge, Abingdon (2016)

    Book  Google Scholar 

  9. Aronson, E., Wilson, T.D., Akert, R.M., Sommers, S.R.: Social Psychology. Pearson, NYC, New York (2018)

    Google Scholar 

  10. Gazzaniga, M.S., Ivry, R.B., Mangun, G.R.: Cognitive Neuroscience. Norton, New York (2019)

    Google Scholar 

  11. Russell, S., Norvig, P.: Artificial Intelligence. Prentice Hall, Upper Saddle River (2020)

    MATH  Google Scholar 

  12. Marsland, S.: Machine Learning. CRC Press, Boca Raton (2015)

    Google Scholar 

  13. Murphy, K.P.: Machine Learning. The MIT Press, Cambridge, Mass (2012)

    Google Scholar 

  14. LeDoux, J.: Rethinking the emotional brain. Neuron 73(4), 653–676 (2012)

    Article  Google Scholar 

  15. Levy, D.J., Glimcher, P.W.: The root of all value: a neural common currency for choice. Current Opinion in Neurobiology 22(6), 1027–1038 (2012)

    Article  Google Scholar 

  16. Berridge, K.C.: ‘Liking’ and “wanting” food rewards: Brain substrates and roles in eating disorders. Physiol. Behav. 97(5), 537–550 (2009)

    Article  Google Scholar 

  17. Glimcher, P.W., Fehr, E.: Neuroeconomics. Academic Press, Oxford (2014)

    Google Scholar 

  18. Kandel, E.R., Koester, J., Mack, S.H., Siegelbaum, S.A.: Principles of Neural Science. McGraw Hill, New York (2021)

    Google Scholar 

  19. Jang, H., Jung, K., Jeong, J., Park, S.K., Kralik, J.D., Jeong, J.: Nucleus accumbens shell moderates preference bias during voluntary choice behavior. Soc Cogn Affect Neurosci 12(9), 1428–1436 (2017)

    Article  Google Scholar 

  20. Kralik, J.D., Xu, E.R., Knight, E.J., Khan, S.A., Levine, W.J.: When less is more: evolutionary origins of the affect heuristic. PLoS ONE 7(10), e46240 (2012)

    Google Scholar 

  21. Kralik, J.D.: Architectural design of mind & brain from an evolutionary perspective. In: Proc. AAAI Fall Sym. Standard Model Mind (2017)

    Google Scholar 

  22. Damasio, A.: Feeling & Knowing. Pantheon, New York (2021)

    Google Scholar 

  23. Meyer, J.S., Quenzer, L.F.: Psychopharmacology. Oxford University Press, Oxford (2019)

    Google Scholar 

  24. Corbetta, M., Shulman, G.L.: Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neuro. 3(3), 201–215 (2002)

    Article  Google Scholar 

  25. Messinger, A., Lebedev, M.A., Kralik, J.D., Wise, S.P.: Multitasking of attention and memory functions in the primate prefrontal cortex. Journal of Neuroscience 29(17), 5640–5653 (2009)

    Article  Google Scholar 

  26. Jung, K., Jeong, J., Kralik, J.D.: A computational model of attention control in multi-attribute, context-dependent decision making. Front. Comput. Neurosci. 13 (2019)

    Google Scholar 

  27. Boland, R., Verduin, M.L.: Synopsis of Psychiatry. Wolters Kluwer, Philadelphia (2022)

    Google Scholar 

  28. Rosch, E.: Principles of categorization. In: Rosch, L. (ed.) Cognition and Categorization, pp. 27–48 (1978)

    Google Scholar 

  29. Kahneman, D.: Thinking, Fast and Slow. Farrar, Straus and Giroux, New York (2011)

    Google Scholar 

  30. Tenenbaum, J.B., Kemp, C., Griffiths, T.L., Goodman, N.D.: How to grow a mind: statistics, structure, and abstraction. Science 331(6022), 1279–1285 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  31. Herrnstein, R.J.: Levels of stimulus control: a functional approach. Cognition 37(1), 133–166 (1990)

    Article  Google Scholar 

  32. Sampson, W.W.L., Khan, S.A., Nisenbaum, E.J., Kralik, J.D.: Abstraction promotes creative problem-solving in rhesus monkeys. Cognition 176, 53–64 (2018)

    Article  Google Scholar 

  33. Lim, S., Yoon, S., Kwon, J., Kralik, J.D., Jeong, J.: Retrospective evaluation of sequential events and the influence of preference-dependent working memory: a computational examination. Front. Comput. Neurosci. 14 (2020)

    Google Scholar 

  34. Wynne, C.D.L., Udell, M.A.R.: Animal Cognition. Palgrave Macmillan, London (2013)

    Book  Google Scholar 

  35. Tomasello, M., Call, J.: Primate Cognition. Oxford University Press, Oxford (1997)

    Google Scholar 

  36. Buss, D.M.: Evolutionary Psychology. Routledge, Abingdon (2019)

    Book  Google Scholar 

  37. Carey, S., Spelke, E.: Domain-specific knowledge and conceptual change. In: Hirschfeld, L.A., Gelman, S.A. (eds.) Mapping the Mind. New York, pp. 169–200 (1994).

    Google Scholar 

  38. Kralik, J.D.: Core high-level cognitive abilities derived from hunter-gatherer shelter building. In: presented at the International Conference on Cognitive Modeling, pp. 49–54 (2018)

    Google Scholar 

  39. Doumas, L.A.A., Hummel, J.E.: Computational models of higher cognition. In: Holyoak, K.J., Morrison, R.G. (eds.) The Oxford Handbook of Thinking and Reasoning, pp. 52–66. Oxford University Press, Oxford (2012)

    Chapter  Google Scholar 

  40. Gross, R.: Being Human. Hodder Education, London (2012)

    Google Scholar 

  41. Kralik, J.D., Mao, T., Cheng, Z., Ray, L.E.: Modeling incubation and restructuring for creative problem solving in robots. Robotics and Autonomous Systems 86, 162–173 (2016)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, South Korea

    Jerald D. Kralik

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  1. Jerald D. Kralik
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Correspondence to Jerald D. Kralik .

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Editors and Affiliations

  1. SingularityNET Foundation, Amsterdam, The Netherlands

    Ben Goertzel

  2. SingularityNET Foundation, Amsterdam, The Netherlands

    Matt Iklé

  3. SingularityNET Foundation, Amsterdam, The Netherlands

    Alexey Potapov

  4. Russian Academy of Sciences, Novosibirsk, Russia

    Denis Ponomaryov

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Kralik, J.D. (2023). Toward a Comprehensive List of Necessary Abilities for Human Intelligence, Part 1: Constructing Knowledge. In: Goertzel, B., Iklé, M., Potapov, A., Ponomaryov, D. (eds) Artificial General Intelligence. AGI 2022. Lecture Notes in Computer Science(), vol 13539. Springer, Cham. https://doi.org/10.1007/978-3-031-19907-3_27

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  • DOI: https://doi.org/10.1007/978-3-031-19907-3_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-19906-6

  • Online ISBN: 978-3-031-19907-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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