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Software


Machine Learning Dynamic Decision Models

With Jonathan Gilligan, a method and software (R and C++) for estimating models of dynamic decision-making that both have strong predictive power and are interpretable in human terms.


Machine Learning for Forecasting Vegetation Health

With Emily Burchfield and Jonathan Gilligan, a decision-support software system in Python that forecasts agricultural productivity at high spatial resolution with models trained on NASA satellite imagery.


Simulating Predictive Models and Trader Behavior in Prediction Markets

With Martin Van der Linden and Jonathan Gilligan, a computational model of a prediction market. Trader agents use forecasting models to trade securities for global temperature anamolies. Implemented in R and Stan.


Sensitivity Analysis for Complex Computational Models

Software package that facilitates sensitivity analysis for complex computational models.

  • Software package website: sa.

Training and Analyzing Simulation Models

Software package that facilitates data-driven agent-based modeling and simulation analysis.


Genetic Programming for Learning Decision Rules

Software package that facilitates data-driven agent-based modeling by estimating computer “programs” (executable functions) that can be used as models of behavior.