Neural Networks Predicting the Winner of a Board Game

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BGG Link:
https://boardgamegeek.com/boardgame/173346/7-wonders-duel

A classification task focused on predicting the winner in the two-player board game, 7 Wonders Duel, using game logs from BoardGameArena.com. Two distinct neural network methodologies were developed. An RNN utilized individual moves as input, predicting outcomes based on sequences within the same match. In contrast, a CNN employed filtered and tokenized game logs, leveraging word embeddings for predictions. Parameter tuning was performed on a training set of 1,011 matches, resulting in the best model achieving over 67% accuracy when trained on a total of 2,168 matches, including an untested final set of 434 matches. This approach has implications for educational game design by reducing early-game futility and offering a more efficient alternative to traditional pedagogical methods.

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