text: Bayesian networks[92] are a tool that can 
  be used for reasoning (using the Bayesian 
  inference algorithm),[g][94] learning (using 
  the 
  expectation–maximization 
  algorithm),[h][96] planning (using decision 
  networks)[97] 
  (using 
  dynamic Bayesian networks).[90] 
  
  perception  and 
  
  Probabilistic algorithms can also be used 
  for filtering, prediction, smoothing, and 
  finding explanations for streams of data, 
  thus helping perception systems analyze 
  processes that occur over time (e.g., hidden 
  Markov models or Kalman filters).[90] 