Bayes Net Demo

Select values for each variable, and then step through the code to compute the joint probability of those values.

Select a value (xi) for each variable (Xi)
Cloudy
Sprinkler
Rainy
Wet Grass

P(C)

+c 0.5
-c 0.5

P(S | C)

+c +s 0.1
-s 0.9
-c +s 0.5
-s 0.5

P(R | C)

+c +r 0.8
-r 0.2
-c +r 0.2
-r 0.8

P(W | S, R)

+s +r +w 0.99
-w 0.01
-r +w 0.9
-w 0.1
-s +r +w 0.9
-w 0.1
-r +w 0.99
-w 0.01

Pseudocode

function bayes_net_joint_probability(bayes_net, x1, x2, x3, x4):

temp_prob = 1:

for Xi in [Cloudy, Sprinkler, Rain, Wet Grass]:

temp_prob = temp_prob * P(Xi | Parents(Xi))

P(x1, x2, x3, x4) = temp_prob

Cloudy Sprinkler Rain Wet Grass Calculated
P(C,S,R,W)
 True
P(C,S,R,W)
+c +s +r +w 0
+c +s +r -w 0
+c +s -r +w 0
+c +s -r -w 0
+c -s +r +w 0
+c -s +r -w 0
+c -s -r +w 0
+c -s -r -w 0
-c +s +r +w 0
-c +s +r -w 0
-c +s -r +w 0
-c +s -r -w 0
-c -s +r +w 0
-c -s +r -w 0
-c -s -r +w 0
-c -s -r -w 0
Local Variables
Variable Value
temp_prob 1
Xi None