A structurally and temporally extended Bayesian belief network model: definitions, properties, and modeling techniques

摘要: We developed the language of Modifiable Temporal Belief Networks (MTBNs) as a structural and temporal extension Bayesian (BNs) to facilitate normative causal modeling under uncertainty. In this paper we present definitions model, its components, fundamental properties. also discuss how represent various types knowledge, with an emphasis on hybrid temporal-explicit time modeling, dynamic structures, avoiding inconsistencies, dealing models that involve simultaneously actions (decisions) non-causal associations. examine relationships among BNs, Networks, MTBNs single granularity, suggest areas application suitable each one them.