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Play-Persona: Modeling Player Behaviour in Computer Games

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lood pressure. Through their patented algorithms they turned the raw data <strong>in</strong>to an engagement<br />

graph so the designers could watch a video of the play<strong>in</strong>g session and spot when the player was<br />

exceed<strong>in</strong>gly frustrated or bored and eventually adjust the layout of the level to fix problems (see<br />

figure 10).<br />

7.1 Weav<strong>in</strong>g <strong>Play</strong>-<strong>Persona</strong>s<br />

Fig. 10 Emsense’s engagement Flow<br />

I suggest revers<strong>in</strong>g this approach and mak<strong>in</strong>g use of hypothetical engagement curves from the very<br />

beg<strong>in</strong>n<strong>in</strong>g to chart out the potential player experiences, as shown <strong>in</strong> figure 11. This has to be done<br />

not for just one play-persona, but for all the ones that the designers want to <strong>in</strong>clude <strong>in</strong> the<br />

phenomenological set of the game. As an example let’s assume that beside the Silent Assass<strong>in</strong> the<br />

designers also chose to reward other play-personas and accommodate for them <strong>in</strong> the design of the<br />

level.<br />

Fig. 11 Pre-emptive <strong>Persona</strong> paths.<br />

102

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