Nettsider med emneord «Multi agent systems»

Economic models used for forecasting and to aid policy decisions have been estimated by the use of data from before the Covid-19 pandemic and the ensuing lockdowns, drop in economic activity and surge in unemployment. An important question for model developers and users is therefore how the empirical relationships that represented normal behavior of firms and households before Covid-19 have been affected by the pandemic and by the policy responses.

A six-year project with the goal to develop and use machine learning to improve the way social scientists can answer classic as well as emerging questions in economics that require the use of large datasets.

Accurate mapping of surface greenhouse gas fluxes is necessary for the validation and calibration of climate models. In this project, we develop a novel framework using drone observations and machine learning to estimate greenhouse gas fluxes at a regional scale.