Abstract
We present an approach to the study of cognitive phenomena by using evolutionary computation. To this end we use a spatial, developmental, neuroevolution system. We use our system to evolve ANNs to perform simple abstractions of the cognitive tasks of color perception and color reading. We define these tasks to explore the nature of the Stroop effect. We show that we can evolve it to perform a variety of cognitive tasks, and also that evolved networks exhibit complex interference behavior when dealing with multiple tasks and incongruent data. We also show that this interference behavior can be manipulated by changing the learning parameters, a method that we successfully use to create a Stroop like interference pattern.
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References
Cantlon, J.F., Platt, M.L., Brannon, E.M.: Beyond the number domain. Trends Cogn. Sci. 13(2), 83–91 (2009)
Eriksen, B.A., Eriksen, C.W.: Effects of noise letters upon the identification of a target letter in a nonsearch task. Percept. Psychophys. 16(1), 143–149 (1974)
Floreano, D., Dürr, P., Mattiussi, C.: Neuroevolution: from architectures to learning. Evol. Intel. 1(1), 47–62 (2008)
Gruau, F.: Automatic definition of modular neural networks. Adapt. Behav. 3(2), 151–183 (1994)
Henik, A., Tzelgov, J.: Is three greater than five: the relation between physical and semantic size in comparison tasks. Mem. Cogn. 10(4), 389–395 (1982). http://dx.doi.org/10.3758/BF03202431
Kashtan, N., Alon, U.: Spontaneous evolution of modularity and network motifs. Proc. Natl. Acad. Sci. USA 102(39), 13773–13778 (2005)
Kashtan, N., Noor, E., Alon, U.: Varying environments can speed up evolution. Proc. Natl. Acad. Sci. 104(34), 13711–13716 (2007)
Katz, G., Benbassat, A., Diesendruck, L., Sipper, M., Henik, A.: From size perception to counting: an evolutionary computation point of view. In: Proceedings of 15th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 1675–1678. ACM (2013)
Kitano, H.: Designing neural networks using genetic algorithms with graph generation system. Complex Syst. J. 4, 461–476 (1990)
Lehman, J., Stanley, K.O.: Abandoning objectives: evolution through the search for novelty alone. Evol. Comput. 19(2), 189–223 (2011)
Secretan, J., Beato, N., Ambrosio, D., Rodriguez, D.B., Campbell, A., Stanley, K.O.: Picbreeder: evolving pictures collaboratively online. In: Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 1759–1768. ACM (2008)
Simon, J.R., Rudell, A.P.: Auditory sr compatibility: the effect of an irrelevant cue on information processing. J. Appl. Psychol. 51(3), 300 (1967)
Stanley, K.O., Miikkulainen, R.: Evolving neural networks through augmenting topologies. Evol. Comput. 10(2), 99–127 (2002)
Stroop, J.R.: Studies of interference in serial verbal reactions. J. Exp. Psychol. 18(6), 643 (1935)
Yosinski, J., Clune, J., Hidalgo, D., Nguyen, S., Zagal, J., Lipson, H.: Evolving robot gaits in hardware: the hyperneat generative encoding vs. parameter optimization. In: Proceedings of 20th European Conference on Artificial Life, pp. 890–897 (2011)
Acknowledgments
The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement number 295644.
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Benbassat, A., Henik, A. (2016). Replicating the Stroop Effect Using a Developmental Spatial Neuroevolution System. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_56
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DOI: https://doi.org/10.1007/978-3-319-45823-6_56
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