“Exploratory Modeling and Analysis (EMA) is a research methodology that uses computational experiments to analyze complex and uncertain systems (Bankes, 1993).That is, exploratory modeling aims at offering computational decision support for decision making under deep uncertainty and Robust decision making.
The EMA workbench is aimed at providing support for doing EMA on models developed in various modelling packages and environments. Currently, we focus on offering support for doing EMA on models developed in Vensim, Excel, and Python. Future plans include support for Netlogo and Repast. The EMA workbench offers support for designing experiments, performing the experiments – including support for parallel processing-, and analysing the results. A key design principle is that people should be able to perform EMA on normal computers, instead of having to take recourse to a HPC.
The Exploratory Modeling and Analysis (EMA) Workbench is an evolving set of tools and methods. It evolved out of code written by Jan Kwakkel for his PhD research. The EMA workbench is implemented in Python and relies on Numpy and Scipy.”