Cognitive Agents and Learning Problems

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Goran Zaharija 1,* Sasa Mladenovic 1 Stefan Dunic 1

1. University of Split, Faculty of science, 21000 Split Croatia

* Corresponding author.


Received: 22 Apr. 2016 / Revised: 11 Aug. 2016 / Accepted: 25 Oct. 2016 / Published: 8 Mar. 2017

Index Terms

Cognitive processes, search algorithms, GOMS model, robots, artificial intelligence


Goals, Operators, Methods, and Selection rules (GOMS) model is a widely recognised concept in Human-Computer Interaction (HCI). Since the initial idea, several GOMS techniques were developed that were used for analysis, differing in their form defined by the logical structure and prediction power. Through defined operators and methods and following the certain rules, the user can reach a specific goal. This work represents an effort to apply GOMS method in the field of artificial intelligence, specifically on a state-space search problems. Card, Morgan, Newman GOMS (CMN-GOMS) model has been chosen, since it represents ground-floor of the GOMS idea that solves the given task through a sequence of operators. Compared with the informed search algorithms for solving the given task, CMN-GOMS model gave better results. Moreover, it was shown that this model could be used in any other space motion problem in the natural environment. LEGO® MINDSTORMS® EV3 robot was used to demonstrate the application of GOMS model in real world pathfinding problems and as a test-bed for comparing proposed model with well-known search algorithms.

Cite This Paper

Goran Zaharija, Saša Mladenović, Stefan Dunić, "Cognitive Agents and Learning Problems", International Journal of Intelligent Systems and Applications (IJISA), Vol.9, No.3, pp.1-7, 2017. DOI:10.5815/ijisa.2017.03.01


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