Using Decision Theory for Player Analysis in Pacman. Cowley, B., Charles, D., Black, M. M, & Hickey, R. J In Yannakakis, G. & Hallam, J., editors, Proceedings of Simulation of Adaptive Behavior 2006, pages 41–50, 2006.
abstract   bibtex   
Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model players dynamically in real- time Pacman (Namco 1980). The method described provides low-level in-game data capture which can provide a simple metric of challenge and player skill, which are key components in measuring the optimality of player experience based on Flow theory. Our approach is based on the calculation of optimal choices available to a player based on key utilities for a given game state. Our hypothesis is that observing a player’s deviation from an expected path can reveal their play preferences and skill, and help enhance our player models. Improved models will then enable in-game adaptation, to better suit individual players. In this paper we outline the basic principle of this approach and discuss the results of our first experiment. Keywords:
@inproceedings{cowley_using_2006,
	title = {Using {Decision} {Theory} for {Player} {Analysis} in {Pacman}},
	abstract = {Computer and videogames have been described using several formal systems – in this paper we consider them as Information Systems. In particular, we use a Decision Theoretic approach to model players dynamically in real- time Pacman (Namco 1980). The method described provides low-level in-game data capture which can provide a simple metric of challenge and player skill, which are key components in measuring the optimality of player experience based on Flow theory. Our approach is based on the calculation of optimal choices available to a player based on key utilities for a given game state. Our hypothesis is that observing a player’s deviation from an expected path can reveal their play preferences and skill, and help enhance our player models. Improved models will then enable in-game adaptation, to better suit individual players. In this paper we outline the basic principle of this approach and discuss the results of our first experiment. Keywords:},
	language = {English},
	booktitle = {Proceedings of {Simulation} of {Adaptive} {Behavior} 2006},
	author = {Cowley, Benjamin and Charles, Darryl and Black, Michaela M and Hickey, Ray J},
	editor = {Yannakakis, Georgios and Hallam, John},
	year = {2006},
	pages = {41--50},
}
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