6.6 Review

The following are the main points you should have learned from this chapter:

  • Probability can be used to make decisions under uncertainty.
  • The posterior probability is used to update an agent's beliefs based on evidence.
  • A Bayesian belief network can be used to represent independence in a domain.
  • Exact inference can be carried out for sparse graphs (with low treewidth).
  • Stochastic simulation can be used for approximate inference.
  • A hidden Markov model or a dynamic belief network can be used for probabilistic reasoning in time, such as for localization.