Our team’s systems game, LOVEBUG, models the spread of the ILOVEYOU computer virus in the 2000s through a mix of system representation and social deduction. Our game offers challenge as its main type of aesthetic. Users compete towards receiving 6 goal points based on their drawn goal cards, and the hacker races towards infecting everyone before any of the users win. We tried to model the system by having social interaction (email) feel exponentially more risky as more people are connected, since the ILOVEYOU bug automatically sent itself to the infected user’s contacts on their address books, and we achieved this by allowing the hacker to indirectly infect others when the hacker and the user are sending emails to the same NPC.
This was a hard game to wrap my head around because I didn’t understand the purpose of the project in the beginning. I didn’t realize that this game didn’t need a learning outcome, and our team felt like we were tripping ourselves over because teaching people about how to avoid computer virus hacks leads to a very different game – something that might not even model the system itself. This is also a hard project in that since there are so many interlinked variables, a small change in the system must be playtested throughly, until the end of the game, to really understand how that small change leads to a shift in the system. Balancing fruity asymmetry was especially challenging since it’s hard to predict the dynamics in our head. Our team went through many many iterations due to our skewed understanding of a systems game at first, but the iteration process felt very rewarding and helped me understand balancing techniques really well. This is also a game that forced me to think in a more minimal manner, since complexity of the game, especially an analogue game, can get out of control really fast if I don’t restrict myself like that. With this constraint, it really forced me to decide what is the core dynamic that our game want to foster, and that ability to simplify down to a core differentiating factor is really useful for anything I might work on.
