#lankveld

Introduction

Players differ in playing strength. In some games, like chess, we honour good players by awarding titles, such as World Champion, International Grand Master, and International Master. In chess, the qualification of differences in playing strength is based on results. Results are expected to reflect the player’s understanding of the game. In contrast to chess, in video games the quantification of the individual differences relies mostly on the behaviour of the players. A player’s behaviour is guided by three processes: (1) cognition (e.g., the player’s thinking during play), (2) perception (e.g., the player’s observations), and (3) the capability with which the player handles the computer and the program.

In video games we observe a player’s behaviour by looking at his input (e.g., mouse clicks and keystrokes). In real life, we can inspect a much larger range of behaviour. Behavioural observation in real life has guided most of the discoveries in the field of psychology. In order to be successful at computer observation we need to consider carefully what we are observing. For instance, a player’s actions can be understood and become meaningful if we relate them to the context in which they are performed. Using collected data we may be able to construct models that help us determine the characteristics of the player. The main aim of this thesis is to develop methods by which we can accurately and automatically quantify individual player differences.

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