A customizable game engine for mobile game-based learning

Authors:
S. Mininel;F. Vatta;S. Gaion;W. Ukovich;M. P. Fanti
Affiliations:
DEEI, University of Trieste, Italy;DEEI, University of Trieste, Italy;DEEI, University of Trieste, Italy;DEEI, University of Trieste, Italy;DEE, Polytechnic of Bari, Italy
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

Evolutionary multiobjective optimization (EMO) is an active research area in the field of evolutionary computation. EMO algorithms are designed to find a non-dominated solution set that approximates the entire Pareto front of a multiobjective optimization ...