Contest

Philip Brookins, Dmitry Ryvkin, and Andrew Smyth. 3/8/2021. “Indefinitely repeated contests: An experimental study.” Experimental Economics . Publisher's Version Abstract

Brookins - Indefinitely Repeated Contests

We experimentally explore indefinitely repeated contests. Theory predicts more cooperation, in the form of lower expenditures, in indefinitely repeated contests with a longer expected time horizon. Our data support this prediction, although this result attenuates with contest experience. Theory also predicts more cooperation in indefinitely repeated contests compared to finitely repeated contests of the same expected length, and we find empirical support for this. Finally, theory predicts no difference in cooperation across indefinitely repeated winner-take-all and proportional-prize contests, yet we find evidence of less cooperation in the latter, though only in longer treatments with more contests played. Our paper extends the experimental literature on indefinitely repeated games to contests and, more generally, contributes to an infant empirical literature on behavior in indefinitely repeated games with “large” strategy spaces.

Philip Brookins and Paan Jindapon. 2/20/2021. “Risk preference heterogeneity in group contests.” Journal of Mathematical Economics. Publisher's Version Abstract

Brookins - Risk Preference Heterogeneity

We analyze the first model of a group contest with players that are heterogeneous in their risk preferences. In our model, individuals’ preferences are represented by a utility function exhibiting a generalized form of constant absolute risk aversion, allowing us to consider any combination of risk-averse, risk-neutral, and risk-loving players. We begin by proving equilibrium existence and uniqueness under both linear and convex investment costs. Then, we explore how the sorting of a compatible set of players by their risk attitudes into competing groups affects aggregate investment. With linear costs, a balanced sorting (i.e., minimizing the variance in risk attitudes across groups) always produces an aggregate investment level that is at least as high as an unbalanced sorting (i.e., maximizing the variance in risk attitudes across groups). Under convex costs, however, identifying which sorting is optimal is more nuanced and depends on preference and cost parameters.

Optimal Prize Structure

One of the strongest design parameters for contests is the prize structure, i.e., the number and level of prizes. In developing best practices, we are working to provide guidance to practitioners to optimize the use of prize funds. Optimal selection of prizes is a complex task. For tasks with diminishing returns to effort (the 100th hour of work improves the output less than the 1st hour),... Read more about Optimal Prize Structure

Robonaut 2 Challenges

The goal of this series of NASA challenges was to create algorithms to train and control Robonaut 2—the first humanoid robot in space. Robonaut 2 is used on the International Space Station (ISS) to help perform dangerous or routine tasks instead of astronauts. Run in 2016, this particular challenge... Read more about Robonaut 2 Challenges

Centers for Medicare & Medicaid Services Challenge Series

This 2013 series of challenges was to develop a software module for the Centers for Medicare & Medicaid Services that could be used across multiple states. Working with the Medicaid office of the state of Minnesota, these challenges developed... Read more about Centers for Medicare & Medicaid Services Challenge Series

ISS-FIT App

Sponsored by NASA, the goal of this 2013 series of challenges was to develop an iPad application for astronauts to use on the International Space Station (ISS) to track food intake. Astronauts on ISS have busy daily schedules and needed a simple way to record what they eat and drink in... Read more about ISS-FIT App

DNA Sequencing Challenge

In collaboration with the Broad Institute, the goal of this 2016 precision medicine contest was to find an algorithm that aligned multiple DNA sequences to a reference DNA for a simpler case. The reference DNA and the DNA from which the sequences originated had only minor differences. The task was to align these sequences fast and accurately,... Read more about DNA Sequencing Challenge

Antibody Clustering Challenge

The goal of this 2015 challenge, conducted in collaboration with the Scripps Research Institute on Topcoder, was to optimize and speed up an existing algorithm for clustering antibody sequences (see the problem statement). Clustering these sequences allows researchers to understand... Read more about Antibody Clustering Challenge

Optimal Design of Contests: Information Revelation in Contests

As part of determining best practices in crowdsourcing, we are working to develop the optimal design of contests by investigating the role of various parameters in contests including number of contestants, matching between tasks and solvers, information revelation, and prize structure.... Read more about Optimal Design of Contests: Information Revelation in Contests

Social Comparison and Contests

In this project, we study the effect of social comparison on inequality in contest environment. We hypothesize that the effects of social comparison on effort will differ for top-performers and bottom-performers in a way that inequality increases, where we consider inequality both in terms of the dispersion of outcomes... Read more about Social Comparison and Contests

EPA ToxCast Predication Challenge

The goal of this 2014 challenge series was to develop a model, based on data provided by the U.S. Environmental Protection Agency, to quantitatively predict a chemical’s systemic Lowest Effect Level (LEL) in a traditional animal toxicity study. The systemic LEL is the lowest dose that shows adverse effects in these animal toxicity tests.... Read more about EPA ToxCast Predication Challenge

EPA Cyanobacteria Predictive Modeling and Mobile App Challenge

The goal of this series of challenges, conducted from August 2013 to January 2015, was to predict the locations and times that the cyanobacteria bloom to occur. Algae are natural components of marine and freshwater flora performing many roles that... Read more about EPA Cyanobacteria Predictive Modeling and Mobile App Challenge

Tech Challenge for Atrocity Prevention

In 2013, USAID and Humanity United tasked competitors to develop an algorithm to predict where and when atrocities would happen in the near future — within the next 30 days — based on the atrocity pre-history from the Political Instability Task Force Data and sociopolitical activities from Global Database of Events, Language, and Tone (see the problem statement). In all, 93 competitors... Read more about Tech Challenge for Atrocity Prevention

Fishing for Fishermen

Sponsored by CoECI in 2016-2017, this series of challenges was to develop an algorithm to help identify and react to illegal, unreported, and unregulated fishing (IUU) (see the problem statement for contest 1; problem statement for contest 2). The first contest drew in 77 competitors who submitted 1,206 submissions while competing for $18,000 in prizes. The top five competitors submitted... Read more about Fishing for Fishermen

U.S. Patent and Trademark Office Algorithm Challenge

Historical patents are a difficult target for digitization. Figures and labels are central to patents and present complex combinations of image and text elements. Sponsored by the CoECI in 2011, the U.S. Patent and Trademark Office (USPTO) Algorithm Challenge tasked competitors... Read more about U.S. Patent and Trademark Office Algorithm Challenge

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