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Classification on Graphs for Dynamic Difficulty Adjustment: More Questions Than Answers AbstractMotivated by a problem of dynamic difficulty adjustment in computer games, we propose a new learning setting. We argue that video games require a mechanism for dynamic difficulty adjustment. Such mechanism can be formulated as a classification problem on a graph that combines the properties of online and active learning. The main contribution of this paper is the clarification of this novel learning setting and a summary of open questions.
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