Software

Machine Learning Dynamic Decision Models

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

• Software package on CRAN: cran.r-project.org/web/packages/datafsm/index.html
• Software package website: datafsm.
• Article in peer-reviewed proceedings: Data-Driven Dynamic Decision Models.

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.

• Software package website: forecastVeg.
• Article describing and applying forecastVeg: arXiv preprint.

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.

• Software package website: predMarket.
• Article describing this software: arXiv preprint.

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.

• Software package website: eat: Empirical Agent Training.

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.

• Software package website: agp: Agent Gentic Programming Software for Data-Driven Modeling.