Influence Diagram and LIMIDS

An influence diagram is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network, in which not only probabilistic inference problems but also decision making problems (following the maximum expected utility criterion) can be modeled and solved. It includes 3 types of nodes: chance, decision and utility nodes (from wikipedia).

PyAgrum’s so-called influence diagram represents both influence diagrams and LIMIDs. The way to enforce that such a model represent an influence diagram and not a LIMID belongs to the inference engine.

Tutorial

Tutorial on Influence Diagram

Input / Output

Influence diagrams can be saved and loaded using the native JGUM / BGUM Format Reference (recommended) or the BIFXML format.

import pyagrum as gum

id_ = gum.fastID("A->C->*D->$U;A->$U")
gum.saveID(id_, "model.jgum")   # jgum (JSON)
gum.saveID(id_, "model.bgum")   # bgum (binary)
id2 = gum.loadID("model.jgum")

Reference