We decided to extend the deadlines for registration and submission for Choice Prediction Competition 2018 (see below for details).

The extended deadlines are:

Registration: June 30th

Submission: July 24th (but see below other important submission dates)

Recall that the competition has two independent tracks. In track “Individual behavior, familiar problems” this submission deadline refers to a file with the predictions, whereas in track “Aggregate behavior, unfamiliar problems” the submission deadline refers to the code (model). For the latter, we will post the competition set on July 25th and participants are required to then submit a file with their predictions by July 28th.

For those who are not familiar with the competition, here is the original call we made (the original deadlines removed to reduce confusion):

We invite you to participate in the 2018 choice prediction competition (“CPC18”) for human decision making. The main goal of this competition is to improve our understanding of the ways by which behavioral decision research can contribute to the derivation of useful predictions of human decision making, above and beyond what is possible using data-driven machine learning tools (if at all possible).

CPC18 distinguishes between two very different prediction tasks: predicting the aggregate population behavior in an unfamiliar choice problem, and predicting the individual behavior in a familiar choice problem. Specifically, CPC18 includes two parallel competition tracks, and you are invited to participate in either one, or better yet, in both. A second goal of the competition is to then understand what type of models are better suited to handle each type of task.

The rules of the competition and further details are given in https://cpc18.wordpress.com. A white paper summarizing the current stage of the competition is provided here.

As in some of the previous choice prediction competitions, the prize for the winners is an invitation to be a co-author of the paper that summarizes the competition.

The competition’s basic idea is as follows. We previously collected a large dataset of human choices between monetary gambles, under risk and under ambiguity, with and without feedback. This dataset includes over 500,000 individual consequential choices. Almost all of this data is publicly available at https://zenodo.org/record/845873#.WeDg9GhSw2x, and can (and probably should) be used to develop and train your predictive models.

In those experiments, each decision maker faced many problems, and the two tracks differ with respect to the exact prediction challenge:

In track “Individual behavior, familiar problems” the task is to predict the individual behavior of a small portion of these decision makers in some of the problems they faced. Therefore, a small portion of the data already collected will be used as the competition data in that track and is thus not available. The goal in this track is to predict, as accurately as possible, the individual behavior reflected in that data.

In track " Aggregate behavior, unfamiliar problems” the task is to predict the aggregate choicerates in a new experiment with new problems that we will run (during March-April 2018). As in some of the previous choice prediction competitions, the submissions should be computer programs that read the parameters of the choice problems as input, and derive the predicted choice rates as output.

We hope that you are up for the challenge!

The organizing team,

Ori Plonsky, Reut Apel, Ido Erev, Eyal Ert, and Moshe Tennenholtz

With apologies for cross-posting.

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