What Can We Do with Bayesian Networks?

• Probabilistic inference: belief update

  • P(E =Y| R = Y, C = Y)

• Probabilistic inference: belief revision

  • Argmax{E,B} P(e, b | C=Y)

• Qualitative inference

  • I(R,C| A)

• Complex inference

  • rational decision making  (influence diagrams)
  • value of information
  • sensitivity analysis

• Causality (analysis under interventions)

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