A Graphical modeling approach to simplifying sequential teams

Abstract

A graphical model for sequential teams is presented. This model is easy to understand, and at the same time, is general enough to model any finite horizon sequential team with finite valued system variables and unconstrained decision rules. The model can also be represented as a directed acyclic factor graph. This representation makes it easier to visualize and understand the functional dependencies between different system variables. It also helps in identifying data that is irrelevant for a decision maker to take an optimal decision. Such irrelevant data can be identified using algorithms from graphical models. Thus, the structural properties of optimal decision makers in this model for a sequential team can be identified in an automated manner using the directed acyclic factor graph representation of the sequential team.