// Bayesian network network "Internal-Network" { //4 variables and 4 probability distributions } variable "Rain" { //2 values type discrete[2] { "False" "True" }; property "position = (151, 235)" ; } variable "Holmes" { //2 values type discrete[2] { "False" "True" }; property "observed True" ; property "position = (235, 328)" ; } variable "Sprinkler" { //2 values type discrete[2] { "False" "True" }; property "position = (314, 234)" ; } variable "Watson" { //2 values type discrete[2] { "False" "True" }; property "observed True" ; property "position = (65, 332)" ; } probability ( "Rain" ) { //1 variable(s) and 2 values table 0.8 0.2 ; } probability ( "Holmes" "Rain" "Sprinkler" ) { //3 variable(s) and 8 values table 1.0 0.1 0.0 0.0 0.0 0.9 1.0 1.0 ; } probability ( "Sprinkler" ) { //1 variable(s) and 2 values table 0.9 0.1 ; } probability ( "Watson" "Rain" ) { //2 variable(s) and 4 values table 0.8 0.0 0.2 1.0 ; }