Towards a hybrid neural and evolutionary heuristic approach for playing tile-matching puzzle games

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Towards a hybrid neural and evolutionary heuristic approach for playing tile-matching puzzle games

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Publication Paper in proceeding
Title Towards a hybrid neural and evolutionary heuristic approach for playing tile-matching puzzle games
Author Font, Jose M ; Manrique, Daniel ; Larrodera, Sergio ; Ramos Criado, Pablo
Date 2017
English abstract
Abstract: 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.
Conference
2017 IEEE Conference on Computational Intelligence and Games (CIG) (22-25 August, 2017 : New York, USA)
DOI https://doi.org/10.1109/CIG.2017.8080418 (link to publisher's fulltext.)
Publisher IEEE
Host/Issue Proceedings of the 2017 IEEE Conference on Computational Intelligence and Games (CIG);
ISBN 978-1-5386-3233-8
Pages 76-79
Language eng (iso)
Subject Games
Neural Networks
Genetic Algorithms
Technology
Research Subject Categories::TECHNOLOGY
Note The Computational Intelligence and Games (CIG) conference series bring... (see Details for more)
Handle http://hdl.handle.net/2043/24153 Permalink to this page
Link http://www.cig2017.com/... (external link to related web page)
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