Cognitive AI Systems Contribute to Improving Creativity Modeling and Measuring Tools

  • Faheem Hassan ZunjaniEmail author
  • Ana-Maria Olteţeanu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11486)


Cognitive science and cognitive psychology have long used creativity tests to measure and investigate the relationships between creativity, creative problem solving and other cognitive abilities. Implementing cognitive systems that can model and/or solve creativity tests can shed light on the cognitive process, and presents the possibility of building much more precise creativity measuring tools. This paper describes four cognitive AI systems related to the Remote Associates Test (RAT) and their contributions to creativity science. comRAT-C is a system that solves the RAT, correlating with human performance. comRAT-G reverse engineers this process to generate RAT queries with a high degree of parameter control. fRAT generates functional RAT queries, resurrecting a theoretical concept proposed by researchers many decades ago. The visual RAT takes advantage of the formal conceptualization necessary for computational implementation, to expand the RAT to the visual domain. All the cognitive systems and generated RAT queries have been successfully validated with human participants and have contributed in improving creativity modeling and measuring tools.


Remote Associates Test Human creativity Visual associates Computational creativity Cognitive systems 


  1. 1.
    Arden, R., Chavez, R.S., Grazioplene, R., Jung, R.E.: Neuroimaging creativity: a psychometric view. Behav. Brain Res. 214(2), 143–156 (2010)CrossRefGoogle Scholar
  2. 2.
    Bowden, E.M., Jung-Beeman, M.: Normative data for 144 compound remote associate problems. Behav. Res. Methods Instrum. Comput. 35(4), 634–639 (2003)CrossRefGoogle Scholar
  3. 3.
    Colton, S., Wiggins, G.A.: Computational creativity: the final frontier? In: Proceedings of the 20th European Conference on Artificial Intelligence, pp. 21–26. IOS Press (2012)Google Scholar
  4. 4.
    Mednick, S.: The associative basis of the creative process. Psychol. Rev. 69(3), 220 (1962)CrossRefGoogle Scholar
  5. 5.
    Mednick, S.A., Mednick, M.: Remote Associates Test: Examiner’s Manual. Houghton Mifflin, Boston (1971)Google Scholar
  6. 6.
    Nelson, D.L., McEvoy, C.L., Schreiber, T.A.: The University of South Florida free association, rhyme, and word fragment norms. Behav. Res. Methods Instrum. Comput. 36(3), 402–407 (2004)CrossRefGoogle Scholar
  7. 7.
    Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge (1994)Google Scholar
  8. 8.
    Olteţeanu, A.M.: Two general classes in creative problem-solving? An account based on the cognitive processes involved in the problem structure - representation structure relationship. In: Proceedings of the International Conference on Computational Creativity, January 2014. Institute of Cognitive Science, Osnabrück (2014)Google Scholar
  9. 9.
    Olteţeanu, A.M.: Proceedings of the Workshop on Computational Creativity, Concept Invention, and General Intelligence (C3GI2016), vol. 1767. CEUR-Ws, Osnabrück (2016)Google Scholar
  10. 10.
    Olteţeanu, A.M., Falomir, Z.: comRAT-C - A computational compound remote associates test solver based on language data and its comparison to human performance. Pattern Recogn. Lett. 67, 81–90 (2015). Scholar
  11. 11.
    Olteţeanu, A.M., Gautam, B., Falomir, Z.: Towards a visual remote associates test and its computational solver. In: Proceedings of the Third International Workshop on Artificial Intelligence and Cognition 2015, vol. 1510, pp. 19–28. CEUR-Ws (2015)Google Scholar
  12. 12.
    Olteţeanu, A.M., Schottner, M., Schuberth, S.: Computationally resurrecting the functional remote associates test using cognitive word associates and principles from a computational solver. Knowl. Based Syst. 168, 1–9 (2019)CrossRefGoogle Scholar
  13. 13.
    Olteţeanu, A.M., Schultheis, H.: What determines creative association? Revealing two factors which separately influence the creative process when solving the remote associates test. J. Creat. Behav. (2017). Scholar
  14. 14.
    Olteţeanu, A.M., Schultheis, H., Dyer, J.B.: Computationally constructing a repository of compound remote associates test items in American English with comRAT-G. Behav. Res. Methods Instrum. Comput. (2017). Scholar
  15. 15.
    Olteţeanu, A.M., Zunjani, F.H.: A visual remote associates test and its validation. Behav. Res. Methods (Submitted)Google Scholar
  16. 16.
    Olteteanu, A.M.: A cognitive systems framework for creative problem solving. Ph.D. thesis, Universität Bremen (2016)Google Scholar
  17. 17.
    Olteţeanu, A.-M.: From simple machines to eureka in four not-so-easy steps: towards creative visuospatial intelligence. In: Müller, V.C. (ed.) Fundamental Issues of Artificial Intelligence. SL, vol. 376, pp. 159–180. Springer, Cham (2016). Scholar
  18. 18.
    Olteţeanu, A.M., Falomir, Z.: Object replacement and object composition in a creative cognitive system. Towards a computational solver of the alternative uses test. Cogn. Syst. Res. 39, 15–32 (2016)CrossRefGoogle Scholar
  19. 19.
    Palermo, D.S., Jenkins, J.J.: Word Association Norms: Grade School Through College (1964)Google Scholar
  20. 20.
    Tucker, A.: Applied Combinatorics. Wiley, Hoboken (2006)zbMATHGoogle Scholar
  21. 21.
    Worthen, B.R., Clark, P.M.: Toward an improved measure of remote associational ability. J. Educ. Meas. 8(2), 113–123 (1971)CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Freie UniversitätBerlinGermany

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