Deep Neural Networks in an ABM Virtual Experiment/David GOLDBAUM

Deep Neural Networks in an ABM Virtual Experiment David GOLDBAUM (Economics Discipline Group, University of Technology Sydney) CCSS School on Computational Social Science Agent-Based Models (ABM) in Economics Friday, January 20, 2023 We use machine learning to model subject decisions in an experiment based on a dynamic game. In this game, players appropriately use prior experiences to inform current decisions. A structural empirical model provides insight into how decisions are informed from prior experiences, but we determine the model to be insufficiently rich to capture decisions well enough to then conduct simulations. Machine learning achieve substantial gains in performance. The role of interactions in determining strategy lends itself to analysis with agent-based modeling. We use the estimated neural network model to run counterfactual virtual simulations that provide information on how well the populations played the game.