BESS - Predicting and Understanding Initial Play (joint with Drew Fudenberg)

Open to the Public
Nador u. 15
101 - Quantum
Wednesday, May 22, 2019 - 11:00am
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Wednesday, May 22, 2019 - 11:00am to 12:15pm

Abstract: We use machine learning to uncover regularities in the initial play of matrix games. We first train a prediction algorithm on data from past experiments. Examining the games where our algorithm predicts correctly, but existing economic models don’t, leads us to add a parameter to the best performing model that improves predictive accuracy. We then observe play in a collection of new “algorithmically-generated” games, and learn that we can obtain even better predictions with a hybrid model that uses a decision tree to decide game-by-game which of two economic models to use for prediction.