Int. J. of Industrial and Systems Engineering   »   2014 Vol.16, No.2

 

 

Title: Improvement of action selection in robots based on learning fuzzy cognitive map and analysis of variance: the case of soccer server simulation environment

 

Authors: Seyed Koosha Golmohammadi; Ali Azadeh; Amir Hossein Gharehgozli; Zeinab Raoofi

 

Addresses:
Department of Electrical and Computer Engineering (ECE), University of Alberta, Edmonton, Alberta, T6G 2V4, Canada
Department of Industrial Engineering, Department of Engineering Optimisation Research and Centre of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, P.O. Box 11365/4563, Iran
Department of Management of Technology and Innovation, Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, 3062 PA Rotterdam, P.O. Box 1738, The Netherlands
Department of Industrial Engineering, Department of Engineering Optimisation Research and Centre of Excellence for Intelligent Based Experimental Mechanics, College of Engineering, University of Tehran, P.O. Box 11365/4563, Iran

 

Abstract: One of the main issues in developing automatic response systems especially autonomous robots is selecting the best action among all possible actions. Fuzzy cognitive maps (FCMs) aim to mimic the reasoning process of the human. FCMs are able to capture and imitate human behaviour by describing, developing and representing models. FCMs are also popular for their simplicity and transparency while being successful in a variety of applications. We developed a novel model that could be used for action selection in robots. This model is constructed on a learning FCM which is relied on improved non-linear Hebbian algorithm. We tested our model through a series of practical experiments on the latest version of Soccer Server Simulation 3D environment. Our tests involved carefully defined factors to measure the team performance. Our results showed a significant improvement in overall performance. The significance of the proposed model was verified by analysis of variance (ANOVA).

 

Keywords: fuzzy cognitive maps; FCM; learning improvement; robot action selection; soccer server simulation; analysis of variance; ANOVA; automatic response systems; autonomous robots; human reasoning; human behaviour; modelling; robot actions; team performance; robot learning.

 

DOI: 10.1504/IJISE.2014.058835

 

Int. J. of Industrial and Systems Engineering, 2014 Vol.16, No.2, pp.184 - 199

 

Available online: 21 Jan 2014

 

 

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