Dynamic Bayesian Network

Dynamic Bayesian Network

• A Bayesian network (BN), which is also called a Bayes net, is a probabilistic graphical model that represents a set of random variables and their probabilistic relationships as a directed acyclic graph
• A dynamic Bayesian network (DBN) extends a standard BN by considering the time evolution of variables and is used to model dynamic systems.
• It is a generalization of the hidden Markov model
• The difference between a hidden Markov model (HMM) and a DBN is that hidden Markov model uses a single hidden state variable to represent the entire state space whereas the DBN represents the hidden state as a set of random variables connected in a graph.
• A DBN allows for the modeling of nonlinear dynamic systems with arbitrary nonlinearities and distributions.

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