Glossary

parameter uncertainty

An uncertainty is a parameter uncertainty if the range is continuous from the lower bound to the upper bound. A parameter uncertainty can be either real valued or discrete valued.

categorical uncertainty

An uncertianty is categorical if there is not a range but a set of possibilities over wich one wants to sample.

uncertainty space

the space created by the set of uncertainties

ensemble

a python class responsible for running a series of computational experiments.

model interface

a python class that provides an interface to an underlying model

working directory

a directory that contains files that a model needs

classification trees

a category of machine learning algorithms for rule induction

prim (patient rule induction method)

a rule induction algorithm

coverage

a metric developed for scenario discovery

density

a metric developed for scenario discovery

scenario discovery

a use case of EMA

case

A case specifies the input parameters for a run of a model. It is a dict instance, with the names of the uncertainties as key, and their sampled values as value.

experiment

An experiment is a complete specification for a run. It specifies the case, the name of the policy, and the name of the model.

policy

a policy is by definition an object with a name attribute. So, policy[‘name’] most return the name of the policy

result

the combination of an experiment and the associated outcomes for the experiment

outcome

the data of interest produced by a model given an experiment