Organizing to Adapt and Compete

Compete to Compute

Local competition among neighboring neurons is common in biological neural networks (NNs). We apply the concept to gradient-based, backprop-trained artificial multilayer NNs. NNs with competing linear units tend to outperform those with non-competing nonlinear units, and avoid catastrophic forgetting when training sets change over time.

To compete or not compete? Ingredients for a successful competition

As the number of competitions in the AI/Robotics field grows larger the question of what is the value of participating becomes more relevant and harder to answer. We look at multiple competition we have participated to, make some observations on them, try to determine what ingredients are needed for a successful competition, and raise questions for the future.

Contracting to compete for flows

5 We present a model in which asset managers design their contracts to attract flows of 6 investor capital. We find that they make their contracts depend on public information, 7 e.g. credit ratings or benchmark indices, as a way to attract flows, rather than as a way 8 to mitigate incentive problems, as has been emphasized in the literature. Unfortunately, 9 asset managers’ competition for flo...

Willingness to Compete: Family Matters

This paper studies the role of family background in explaining differences in the willingness to compete. By combining data from a lab experiment conducted with a representative sample of adolescents in Norway and high quality register data on family background, we show that family background is fundamental in two important ways. First, boys from low socioeconomic status families are less willi...

Rac and Rho compete to cooperate