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DIS
2009
Springer

Player Modeling for Intelligent Difficulty Adjustment

8 years 3 months ago
Player Modeling for Intelligent Difficulty Adjustment
In this paper we aim at automatically adjusting the difficulty of computer games by clustering players into different types and supervised prediction of the type from short traces of gameplay. An important ingredient of video games is to challenge players by providing them with tasks of appropriate and increasing difficulty. How this difficulty should be chosen and increase over time strongly depends on the ability, experience, perception and learning curve of each individual player. It is a subjective parameter that is very difficult to set. Wrong choices can easily lead to players stopping to play the game as they get bored (if underburdened) or frustrated (if overburdened). An ideal game should be able to adjust its difficulty dynamically governed by the player's performance. Modern video games utilise a game-testing process to investigate among other factors the perceived difficulty for a multitude of players. In this paper, we investigate how local models can be combined to a...
Olana Missura, Thomas Gärtner
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where DIS
Authors Olana Missura, Thomas Gärtner
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