Predicting and understanding initial play

Drew Fudenberg, Annie Liang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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.Wethenobserveplayinacollectionofnew“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.

Original languageEnglish (US)
Pages (from-to)4112-4141
Number of pages30
JournalAmerican Economic Review
Volume109
Issue number12
DOIs
StatePublished - Dec 2019
Externally publishedYes

ASJC Scopus subject areas

  • Economics and Econometrics

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