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1. Clustering and Classification of Time Series in Real-Time Strategy Games - A machine learning approach for mapping StarCraft II games to clusters of game state time series while limited by fog of war
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Real-time strategy (RTS) games feature vast action spaces and incomplete information, thus requiring lengthy training times for AI-agents to master them at the level of a human expert. Based on the inherent complexity and the strategical interplay between the players of an RTS game, it is hypothesized that data sets of played games exhibit clustering properties as a result of the actions made by the players. LÄS MER
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