Play-Persona: Modeling Player Behaviour in Computer Games
Play-Persona: Modeling Player Behaviour in Computer Games
Play-Persona: Modeling Player Behaviour in Computer Games
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a secondary variable together with the location po<strong>in</strong>t data. These types of plots are useful to<br />
<strong>in</strong>vestigate where players are <strong>in</strong>jured and the causes.<br />
3) Crouch and cover: The (X,Y,Z)-coord<strong>in</strong>ates for the locations where the player crouches or uses<br />
the snap-to-cover system that is a hallmark of Kane & Lynch.<br />
4) Speed: The movement modifier of the players, i.e. whether the player was stand<strong>in</strong>g still,<br />
walk<strong>in</strong>g, runn<strong>in</strong>g etc.<br />
By plott<strong>in</strong>g the navigation coord<strong>in</strong>ates on top of the perfect path, <strong>in</strong> ArcGIS it is possible to<br />
calculate the extent to which players follow this path (Figure 5), i.e. behave as <strong>in</strong>tended by the<br />
design. In the example provided here, roughly 85% of the player’s path falls with<strong>in</strong> the 2-meter<br />
perfect path, i.e. the player is more or less behav<strong>in</strong>g as <strong>in</strong>tended with respect to navigation. The<br />
same procedure can be run with data from thousands of players at the same time plotted on top of<br />
the perfect path. If such datasets are available, it becomes especially valuable to exam<strong>in</strong>e if there<br />
are sections where numerous po<strong>in</strong>ts or clusters of navigation po<strong>in</strong>ts fall outside the perfect path, as<br />
it <strong>in</strong>dicates a deviation by a substantial number of players from the <strong>in</strong>tended path/-s.<br />
In order to address the second question, if there are areas where the player is heavily challenged,<br />
the health of the players was added as a color code on top of the navigation po<strong>in</strong>t data. The<br />
analysis showed that for this segment of the game level, the player went mostly un<strong>in</strong>jured or lightly<br />
<strong>in</strong>jured. However, <strong>in</strong> two positions the player´s health drops rapidly, and often players would die <strong>in</strong><br />
these locations. These are locations where considerable opposition is supplied via AI-controlled<br />
opponents (Figure 6). This analysis assists <strong>in</strong> clarify<strong>in</strong>g whether the level is too hard to play<br />
(players often dy<strong>in</strong>g/gett<strong>in</strong>g <strong>in</strong>jured heavily), or too easy. Conversely, if there is a good balance <strong>in</strong><br />
the level between easy and hard segments (a typical design goal for shooter-type games). The use<br />
of crouch<strong>in</strong>g and the cover system was also exam<strong>in</strong>ed, as was the speed with which the player<br />
moved through the level. Dur<strong>in</strong>g most of the <strong>in</strong>vestigated segment, movement was rapid, which<br />
corresponds with the player not be<strong>in</strong>g substantially challenged. However, <strong>in</strong> the two “trouble spots”<br />
the player would slow down to a standstill and take cover, navigat<strong>in</strong>g between different cover<br />
options <strong>in</strong> order to elim<strong>in</strong>ate the opposition. The analysis showed that for the first “trouble spot”,<br />
the players generally take little cover; however, cover is also more scarcely available.<br />
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