Gibbs-Ask.md

GIBBS-ASK

AIMA3e

function GIBBS-ASK(X, e, bn, N) returns an estimate of P(X | e)
 local variables: N, a vector of counts for each value of X, initially zero
        Z, the nonevidence variables in bn
        x, the current state of the network, initially copied from e

 initialize x with random values for the variables in Z
 for j = 1 to N do
   for each Z_i in Z do
     set the value of Z_i in x by sampling from P(Z_i | mb(Z_i))
     N[x] ← N[x] + 1 where x is the value of X in x
 return NORMALIZE(N)

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Figure ?? The Gibbs sampling algorithm for approximate inference in Bayesian networks; this version cycles through the variables, but choosing variables at random also works.

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AIMA4e

function GIBBS-ASK(X, e, bn, N) returns an estimate of P(X | e)
 local variables: N, a vector of counts for each value of X, initially zero
        Z, the nonevidence variables in bn
        x, the current state of the network, initially copied from e

 initialize x with random values for the variables in Z
 for j = 1 to N do
   choose any variable Z_i from Z acoording to any distribution ρ(i)
     set the value of Z_i in x by sampling from P(Z_i | mb(Z_i))
     N[x] ← N[x] + 1 where x is the value of X in x
 return NORMALIZE(N)

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Figure ?? The Gibbs sampling algorithm for approximate inference in Bayesian networks; this version cycles through the variables, but choosing variables at random also works.