Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
381915 | Entertainment Computing | 2014 | 12 Pages |
Game designers spend a great deal of time developing well-balanced game experiences. However, differences in player ability, hardware capacity (e.g. network connections) or game mechanic constraints make it difficult to balance games for all players in all conditions. Adaptive balancing systems have been employed in an attempt to automatically compensate for these differences in real time as the game is being played. However, due to the complex non-linear mechanics underlying modern games, automated balancing systems can be highly unstable for all but the simplest mechanics, restricting the design space. In prior work we advanced the concept of using adaptive minigames deployed from within a larger game to decouple the adaptive mechanics from the main game mechanics. In particular, we looked at time-adaptive minigames (ATMs) which attempt to control the time to completion of a minigame. In this paper, we extend the ATM framework with additional time-adaptation algorithms and analyze the interaction between adaptive algorithm, game mechanic, and game difficulty in a controlled experiment. We find significant effects and interactions for all three factors, confirming our intuition that these processes are important and linked. We further find that finer temporal granularity leads to less-perceptible adaptation and smaller deviations in game completion times. This work provides an empirically-grounded algorithmic foundation for the design and practical deployment of ATMs in larger games, a foundation that can improve the balance and experience in these games.