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Title: Player modeling using self-organization in Tomb Raider : Underworld
Authors: Drachen, Anders
Canossa, Alessandro
Yannakakis, Georgios N.
Keywords: Computer simulation
Video games
Human-computer interaction
Level design (Computer science)
Issue Date: 2009
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Drachen, A., Canossa, A., & Yannakakis, G. N. (2009). Player modeling using self-organization in Tomb Raider: Underworld. IEEE Symposium on Computational Intelligence and Games, Milan.
Abstract: We present a study focused on constructing models of players for the major commercial title Tomb Raider: Underworld (TRU). Emergent self-organizing maps are trained on high-level playing behavior data obtained from 1365 players that completed the TRU game. The unsupervised learning approach utilized reveals four types of players which are analyzed within the context of the game. The proposed approach automates, in part, the traditional user and play testing procedures followed in the game industry since it can inform game developers, in detail, if the players play the game as intended by the game design. Subsequently, player models can assist the tailoring of game mechanics in real-time for the needs of the player type identified.
Appears in Collections:Scholarly Works - InsDG

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