Player role identification in the online social deduction game Werewolf has been a common research topic in the past decade. Among Us, a fairly new online social deduction game, gained a lot of popularity recently. Given the popularity of the game, an opportunity arises to extract information on social deduction. This research focuses on extracting information from emergency meetings in Among Us and subsequently using this information to automatically detect player roles. First, a framework is presented that can be used to extract information from videos with gameplay of Among Us. This framework can extract the chat messages from the emergency meetings, detect imposters at the end of the game, and extract voting data. Secondly, the framework is used to process videos with 59 games of Among Us gameplay. The data produced by the framework will be normalized and transformed into numerical data using term frequency-inverse document frequency (tf-idf), Finally, two types of Support Vector Machines (SVM) and a Naive Bayes classifier are used to automatically detect player roles. We show that detecting player roles is a difficult yet learnable challenge.

StarCraft is a Real-Time Strategy game, which has a large state-space, is played in real-time, and commonly features two opposing players, capable of acting simultaneously. One of the aspects of the game is building walls. In this paper, we present an algorithm that can be used for wall building for an agent playing the game of StarCraft: Brood War.

StarCraft is a real-time strategy game, which has a large state space, and commonly features two opposing players, capable of acting simultaneously. One of the aspects of the game is resource gathering. Each agent playing StarCraft has to gather minerals from nearby mineral field in order to produce more units. The more resources can be gathered, the larger the army is to attack the opponent and win the game. We present five algorithms that can be used for resource gathering for an intelligent agent playing the game of StarCraft: Brood War. The results reveal that improving the scheduling or the path finding improve the resource gathering considerably.