Artificial Intelligence Applications and Innovations AIAI 2012 International Workshops: AIAB, AIeIA, CISE, COPA, IIVC, ISQL, MHDW, and WADTMB Halkidiki, Greece, September 27-30, 2012, Part II
Conference papers
Player Modeling Using HOSVD towards Dynamic Difficulty Adjustment in Videogames
Abstract : In this work, we propose and evaluate a Higher Order Singular Value Decomposition (HOSVD) of a tensor as a means to classify player behavior and adjust game difficulty dynamically. Applying this method to player data collected during a plethora of game sessions resulted in a reduction of the dimensionality of the classification problem and a robust classification of player behavior. Simultaneously HOSVD was able to perform significant data compression without significant reduction as regards to the accuracy of the classification outcome and furthermore, was able to alleviate the data sparseness problem common within data collected from game sessions.
https://hal.archives-ouvertes.fr/hal-01523082
Contributor : Hal Ifip <>
Submitted on : Tuesday, May 16, 2017 - 9:17:17 AM Last modification on : Tuesday, September 22, 2020 - 1:50:04 PM Long-term archiving on: : Friday, August 18, 2017 - 12:15:57 AM
Kostas Anagnostou, Manolis Maragoudakis. Player Modeling Using HOSVD towards Dynamic Difficulty Adjustment in Videogames. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.125-134, ⟨10.1007/978-3-642-33412-2_13⟩. ⟨hal-01523082⟩