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DC Field | Value | Language |
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dc.contributor.author | Yannakakis, Georgios N. | - |
dc.contributor.author | Hallam, John | - |
dc.date.accessioned | 2018-05-03T09:35:24Z | - |
dc.date.available | 2018-05-03T09:35:24Z | - |
dc.date.issued | 2007-04 | - |
dc.identifier.citation | Yannakakis, G. N., & Hallam, J. (2007). Game and player feature selection for entertainment capture. IEEE Symposium on Computational Intelligence and Games (CIG), 2007, Honolulu. 244-251. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar//handle/123456789/29731 | - |
dc.description | The authors would like to thank Henrik Jorgensen and all children of Henriette Horlucks and Rosengardskolen Schools, Odense, Denmark that participated in the experiments. The tiles were designed by C. Isaksen from Isaksen Design and parts of their hardware and software implementation were collectively done by A. Derakhshan, F. Hammer, T. Klitbo and J. Nielsen. KOMPAN, Mads Clausen Institute, and Danfoss Universe also participated in the development of the tiles. | en_GB |
dc.description.abstract | The notion of constructing a metric of the degree to which a player enjoys a given game has been presented previously. In this paper, we attempt to construct such metric models of children’s ‘fun’ when playing the Bug Smasher game on the Playware platform. First, a set of numerical features derived from a child’s interaction with the Playware hardware is presented. Then the Sequential Forward Selection and the n- Best feature selection algorithms are employed together with a function approximator based on an artificial neural network to construct feature sets and function that model the child’s notion of ‘fun’ for this game. Performance of the model is evaluated by the degree to which the preferences predicted by the model match those expressed by the children in a survey experiment. The results show that an effective model can be constructed using these techniques and that the Sequential Forward Selection method performs better in this task than n-Best. The model reveals differing preferences for game parameters between children who react fast to game events and those who react slowly. The limitations and the use of the methodology as an effective adaptive mechanism to entertainment augmentation are discussed. | en_GB |
dc.description.sponsorship | This work was in part supported by the Danish National Research Council (project no: 274-05-0511). | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | Computer games -- Case studies | en_GB |
dc.subject | Human-computer interaction | en_GB |
dc.subject | Neural networks (Computer science) | en_GB |
dc.title | Game and player feature selection for entertainment capture | en_GB |
dc.type | conferenceObject | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.bibliographicCitation.conferencename | IEEE Symposium on Computational Intelligence and Games (CIG 2007) | en_GB |
dc.bibliographicCitation.conferenceplace | Honolulu, HI, USA, 01-05/04/2007 | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1109/CIG.2007.368105 | - |
Appears in Collections: | Scholarly Works - InsDG |
Files in This Item:
File | Description | Size | Format | |
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Game_and_player_feature_selection_for_entertainment_capture_2007.pdf | 2.02 MB | Adobe PDF | View/Open |
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