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Found 6 papers, 1 papers with code
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
The power of a platform is limited to controlling representations -- the subset of information about items presented by default to users.
Learning When to Advise Human Decision Makers
Artificial intelligence (AI) systems are increasingly used for providing advice to facilitate human decision making in a wide range of domains, such as healthcare, criminal justice, and finance.
From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions
Recently, it was demonstrated that a new estimation method called "quantal regret" produces more accurate estimates for human agents than the classic approach that assumes that agents are rational and reach a Nash equilibrium; however, this method has not been compared to methods that take into account behavioral aspects of human play.
Bid Prediction in Repeated Auctions with Learning
We consider the problem of bid prediction in repeated auctions and evaluate the performance of econometric methods for learning agents using a dataset from a mainstream sponsored search auction marketplace.
Neural Networks for Predicting Human Interactions in Repeated Games
We show that if the available input is only of a short sequence of play, economic information about the game is important for predicting behavior of human agents.
Behavior-Based Machine-Learning: A Hybrid Approach for Predicting Human Decision Making
A large body of work in behavioral fields attempts to develop models that describe the way people, as opposed to rational agents, make decisions.
