Scientists at Gwangju Institute of Science and Technology have developed a new AI-powered Dynamic Difficulty Adjustment (DDA) method that focuses on players’ emotions and adjusts the difficulty level in real-time to maximize their satisfaction. This will contribute to balancing the difficulty of games and making them more appealing to players have all types.
One example of this DDA method would be is if a player’s performance exceeds the developer’s expectations for a given difficulty level, the agent can automatically raise the difficulty to increase the challenge level. A caveat of this strategy is that only player performance is taken into account, not how much fun they are actually having. During a test with 20 volunteers, the scientists verified that the DDA agents could produce AIs that improved the players’ overall experience in a fighting game, regardless of their challenge level. Thankfully, there’s still this Nintendo Game Boy turned DMG-0B that won’t have to deal with DDA.
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One advantage of our approach over other emotion-centered methods is that it does not rely on external sensors, such as electroencephalography. Once trained, our model can estimate player states using in-game features only. Commercial game companies already have huge amounts of player data. They can exploit these data to model the players and solve various issues related to game balancing using our approach,” said Kyung-Joong Kim, Associate Professor, who led the study.
