1. A method for analyzing a probabilistic graphical model, comprising: by a back-end server component, retrieving a logical graph model, the logical graph model having one or more variables wherein each variable is represented as a logical class with attributes, wherein the logical graph model includes variables of the probabilistic graphical model; selecting a variable in the logical graph model and comparing the selected variable to other variables in the logical graph model; generating, for the one or more variables in the logical graph model, a value subclass for each of a variable's scenarios when a user asserts discrete scenarios for the variable; generating, for each variable, index subclasses, each index subclass having at least one attribute comprised of a property and an object, the latter a subclass of an index object class; asserting at least one scenario or factor for the variable; creating edges with labels between the variables of the logical graph model, wherein the labeled edges correspond to influence relationships in the probabilistic graphical model, wherein the labels include “influences” and “influenced by” inverse properties; and creating additional index subclasses for the one or more variables of the logical graph model, wherein the additional index subclasses of the one or more variables are influenced by additional index subclasses of one or more other variables in the probabilistic graphical model; and automatically generating relationships between variables, wherein the back-end server component is configured to interact with a front-end user computing device, the front end user computing device configured to allow a user to employ the logical graph model to create, edit, and browse the assertions and inferences of the probabilistic graphical model.