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Year: 2012

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Type: Proceedings

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Title: Machine Learning Algorithms for Player Satisfaction Optimization

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Author: Bojkovski, Nenad
Author: Madevska Bogdanova, Ana

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Abstract: There are several state-of-the-art algorithms currently used for optimization of various aspects of games affecting player satisfaction. In this paper we give a survey of these methods in order to present the platform of research for modeling player satisfaction for a generic player. We focus on the systems for optimization of overall player experience possible applicable on more genres of games. The algorithms are used for optimization of Non-Player Characters (NPC) behavior, Content Generation, Dynamic Difficulty Adjustment (DDA) etc.

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Publisher: Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia

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Relation: The 9th Conference for Informatics and Information Technology (CIIT 2012)

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Identifier: oai:repository.ukim.mk:20.500.12188/24352
Identifier: http://hdl.handle.net/20.500.12188/24352

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