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Descripción
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| In this paper we explore the hybrid application of evolutionary computation and artificial neural networks in the development of intelligent systems able to solve the problem of approximating the optimal strategy in a tile-matching puzzle game. Three intelligent systems are proposed: an evolutionary heuristic technique, artificial neural networks, and a hybrid approach that combines both. Results show that the hybrid approach, which combines the advantages of the two previous solutions, performs better at both, the number of completed lines and the average piece placement time. These results aim to serve as the basis for a later comparative study against state- of-the-art techniques in the topic. | |
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Internacional
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Si |
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Nombre congreso
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IEEE Conference on Computational Intelligence and Games 2017 |
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Tipo de participación
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960 |
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Lugar del congreso
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New York, USA |
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Revisores
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Si |
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ISBN o ISSN
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978-1-5386-3234-5 |
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DOI
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10.1109/CIG.2017.8080418 |
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Fecha inicio congreso
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22/08/2017 |
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Fecha fin congreso
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25/08/2017 |
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Desde la página
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76 |
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Hasta la página
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79 |
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Título de las actas
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2017 IEEE Conference on Computational Intelligence and Games (CIG), |