Multi Entity Bayesian Logic

Subject classification: this is a statistics resource.


MEBN is breakthrough Bayesian reasoning system in which complex probabilistics models are constructed from modular components that can be replicated and combined in an infinite variety of ways.MEBN allows models to capture important and subtle aspects of objects and their inter-relationships that would be impossible to model using existing technologies.


MEBN logic represent the world as comprised of entities that have attributes and are related to other entities.Random variables represent features of entities and relationships among entities.MEBN logic expresses knowledge about attributes and relationships as a collection of MEBN fragments (MFrags) organized into MEBN Theories (MTheories).

An MFrag represents a conditional probabilty distribution for instances of its resident random variables given their parents in the fragment graph and the context node.

An MTheory is a set of MFrags that collectively satisfies consistency constraints ensuring the existence of a unique joint probability distribution over instances of the random variables represented in each of the MFRAGS within the set.