// Bayesian Network // Elvira format bnet Unknown { // Network Properties version = 1.0; default node states = (absent , present); // Network Variables node GoodStudent(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node Age(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 3; states = (Adolescent Adult Senior); } node SocioEcon(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Prole Middle UpperMiddle Wealthy); } node RiskAversion(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Psychopath Adventurous Normal Cautious); } node VehicleYear(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (Current Older); } node ThisCarDam(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (None Mild Moderate Severe); } node RuggedAuto(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 3; states = (EggShell Football Tank); } node Accident(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (None Mild Moderate Severe); } node MakeModel(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 5; states = (SportsCar Economy FamilySedan Luxury SuperLuxury); } node DrivQuality(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 3; states = (Poor Normal Excellent); } node Mileage(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (FiveThou TwentyThou FiftyThou Domino); } node Antilock(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node DrivingSkill(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 3; states = (SubStandard Normal Expert); } node SeniorTrain(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node ThisCarCost(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Thousand TenThou HundredThou Million); } node Theft(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node CarValue(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 5; states = (FiveThou TenThou TwentyThou FiftyThou Million); } node HomeBase(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Secure City Suburb Rural); } node AntiTheft(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node PropCost(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Thousand TenThou HundredThou Million); } node OtherCarCost(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Thousand TenThou HundredThou Million); } node OtherCar(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node MedCost(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Thousand TenThou HundredThou Million); } node Cushioning(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Poor Fair Good Excellent); } node Airbag(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 2; states = (True False); } node ILiCost(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 4; states = (Thousand TenThou HundredThou Million); } node DrivHist(finite-states) { kind-of-node = chance; type-of-variable = finite-states; relevance = 7.0; num-states = 3; states = (Zero One Many); } // links of the associated graph: link SocioEcon GoodStudent; link Age GoodStudent; link Age SocioEcon; link Age RiskAversion; link SocioEcon RiskAversion; link SocioEcon VehicleYear; link RiskAversion VehicleYear; link Accident ThisCarDam; link RuggedAuto ThisCarDam; link MakeModel RuggedAuto; link VehicleYear RuggedAuto; link Antilock Accident; link Mileage Accident; link DrivQuality Accident; link SocioEcon MakeModel; link RiskAversion MakeModel; link DrivingSkill DrivQuality; link RiskAversion DrivQuality; link MakeModel Antilock; link VehicleYear Antilock; link Age DrivingSkill; link SeniorTrain DrivingSkill; link Age SeniorTrain; link RiskAversion SeniorTrain; link ThisCarDam ThisCarCost; link CarValue ThisCarCost; link Theft ThisCarCost; link AntiTheft Theft; link HomeBase Theft; link CarValue Theft; link MakeModel CarValue; link VehicleYear CarValue; link Mileage CarValue; link RiskAversion HomeBase; link SocioEcon HomeBase; link RiskAversion AntiTheft; link SocioEcon AntiTheft; link OtherCarCost PropCost; link ThisCarCost PropCost; link Accident OtherCarCost; link RuggedAuto OtherCarCost; link SocioEcon OtherCar; link Accident MedCost; link Age MedCost; link Cushioning MedCost; link RuggedAuto Cushioning; link Airbag Cushioning; link MakeModel Airbag; link VehicleYear Airbag; link Accident ILiCost; link DrivingSkill DrivHist; link RiskAversion DrivHist; //Network Relationships: relation Age { values= table (0.2 0.6 0.2 ); } relation GoodStudent SocioEcon Age { values= table (0.1 0.0 0.0 0.2 0.0 0.0 0.5 0.0 0.0 0.4 0.0 0.0 0.9 1.0 1.0 0.8 1.0 1.0 0.5 1.0 1.0 0.6 1.0 1.0 ); } relation SocioEcon Age { values= table (0.4 0.4 0.5 0.4 0.4 0.2 0.19 0.19 0.29 0.01 0.01 0.01 ); } relation RiskAversion Age SocioEcon { values= table (0.02 0.02 0.02 0.02 0.015 0.015 0.015 0.015 0.01 0.01 0.01 0.01 0.58 0.38 0.48 0.58 0.285 0.185 0.285 0.285 0.09 0.04 0.09 0.09 0.3 0.5 0.4 0.3 0.5 0.6 0.5 0.4 0.4 0.35 0.4 0.4 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.3 0.5 0.6 0.5 0.5 ); } relation VehicleYear SocioEcon RiskAversion { values= table (0.15 0.15 0.15 0.15 0.3 0.3 0.3 0.3 0.8 0.8 0.8 0.8 0.9 0.9 0.9 0.9 0.85 0.85 0.85 0.85 0.7 0.7 0.7 0.7 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 ); } relation ThisCarDam Accident RuggedAuto { values= table (1.0 1.0 1.0 0.0010 0.2 0.7 1.0E-6 0.0010 0.05 1.0E-6 1.0E-6 0.05 0.0 0.0 0.0 0.9 0.75 0.29 9.99E-4 0.099 0.6 9.0E-6 9.99E-4 0.2 0.0 0.0 0.0 0.098 0.049999 0.009999 0.7 0.8 0.3 9.0E-5 0.0090 0.2 0.0 0.0 0.0 0.0010 1.0E-6 1.0E-6 0.299 0.1 0.05 0.9999 0.99 0.55 ); } relation RuggedAuto MakeModel VehicleYear { values= table (0.95 0.95 0.5 0.9 0.2 0.05 0.1 0.1 0.05 0.05 0.04 0.04 0.5 0.1 0.6 0.55 0.6 0.6 0.55 0.55 0.01 0.01 0.0 0.0 0.2 0.4 0.3 0.3 0.4 0.4 ); } relation Accident Antilock Mileage DrivQuality { values= table (0.7 0.99 0.999 0.4 0.98 0.995 0.3 0.97 0.99 0.2 0.95 0.985 0.6 0.98 0.995 0.3 0.96 0.99 0.2 0.95 0.98 0.1 0.94 0.98 0.2 0.0070 7.0E-4 0.3 0.01 0.0030 0.3 0.02 0.0070 0.2 0.03 0.01 0.2 0.01 0.0030 0.2 0.02 0.0070 0.2 0.03 0.01 0.1 0.03 0.01 0.07 0.0020 2.0E-4 0.2 0.0050 0.0010 0.2 0.0070 0.0020 0.3 0.01 0.0030 0.1 0.0050 0.0010 0.2 0.015 0.0020 0.2 0.015 0.0050 0.3 0.02 0.0070 0.03 0.0010 1.0E-4 0.1 0.0050 0.0010 0.2 0.0030 0.0010 0.3 0.01 0.0020 0.1 0.0050 0.0010 0.3 0.0050 0.0010 0.4 0.0050 0.0050 0.5 0.01 0.0030 ); } relation MakeModel SocioEcon RiskAversion { values= table (0.1 0.1 0.1 0.1 0.15 0.15 0.15 0.15 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.7 0.7 0.7 0.7 0.2 0.2 0.2 0.2 0.05 0.05 0.05 0.05 0.01 0.01 0.01 0.01 0.2 0.2 0.2 0.2 0.65 0.65 0.65 0.65 0.3 0.3 0.3 0.3 0.09 0.09 0.09 0.09 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.45 0.45 0.45 0.45 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 0.2 0.2 ); } relation DrivQuality DrivingSkill RiskAversion { values= table (1.0 1.0 1.0 1.0 0.5 0.3 0.0 0.0 0.3 0.01 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.4 1.0 0.8 0.2 0.01 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.3 0.0 0.2 0.5 0.98 1.0 1.0 ); } relation Mileage { values= table (0.1 0.4 0.4 0.1 ); } relation Antilock MakeModel VehicleYear { values= table (0.9 0.1 0.0010 0.0 0.4 0.0 0.99 0.3 0.99 0.15 0.1 0.9 0.999 1.0 0.6 1.0 0.01 0.7 0.01 0.85 ); } relation DrivingSkill Age SeniorTrain { values= table (0.5 0.5 0.3 0.3 0.1 0.4 0.45 0.45 0.6 0.6 0.6 0.5 0.05 0.05 0.1 0.1 0.3 0.1 ); } relation SeniorTrain Age RiskAversion { values= table (0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0E-6 1.0E-6 0.3 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.999999 0.999999 0.7 0.1 ); } relation ThisCarCost ThisCarDam CarValue Theft { values= table (0.2 1.0 0.05 1.0 0.04 1.0 0.04 1.0 0.04 1.0 0.15 0.95 0.03 0.95 0.03 0.99 0.03 0.99 0.02 0.98 0.05 0.25 0.01 0.15 0.0010 0.01 0.0010 0.0050 0.0010 0.0030 0.03 0.05 1.0E-6 0.01 1.0E-6 0.0050 1.0E-6 0.0010 1.0E-6 1.0E-6 0.8 0.0 0.95 0.0 0.01 0.0 0.01 0.0 0.01 0.0 0.85 0.05 0.97 0.05 0.02 0.01 0.02 0.01 0.03 0.01 0.95 0.75 0.99 0.85 0.0010 0.01 0.0010 0.0050 0.0010 0.0030 0.97 0.95 0.999999 0.99 1.0E-6 0.0050 1.0E-6 0.0010 1.0E-6 1.0E-6 0.0 0.0 0.0 0.0 0.95 0.0 0.95 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.95 0.0 0.95 0.0 0.25 0.01 0.0 0.0 0.0 0.0 0.998 0.98 0.998 0.99 0.018 0.044 0.0 0.0 0.0 0.0 0.999998 0.99 0.999998 0.998 0.009998 0.029998 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.75 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.98 0.95 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.99 0.97 ); } relation Theft AntiTheft HomeBase CarValue { values= table (1.0E-6 2.0E-6 3.0E-6 2.0E-6 1.0E-6 5.0E-4 0.0020 0.0050 0.0050 1.0E-6 1.0E-5 1.0E-4 3.0E-4 3.0E-4 1.0E-6 1.0E-5 2.0E-5 5.0E-5 5.0E-5 1.0E-6 1.0E-6 2.0E-6 3.0E-6 2.0E-6 1.0E-6 0.0010 0.0050 0.01 0.01 1.0E-6 1.0E-5 2.0E-4 5.0E-4 5.0E-4 1.0E-6 1.0E-5 1.0E-4 2.0E-4 2.0E-4 1.0E-6 0.999999 0.999998 0.999997 0.999998 0.999999 0.9995 0.998 0.995 0.995 0.999999 0.99999 0.9999 0.9997 0.9997 0.999999 0.99999 0.99998 0.99995 0.99995 0.999999 0.999999 0.999998 0.999997 0.999998 0.999999 0.999 0.995 0.99 0.99 0.999999 0.99999 0.9998 0.9995 0.9995 0.999999 0.99999 0.9999 0.9998 0.9998 0.999999 ); } relation CarValue MakeModel VehicleYear Mileage { values= table (0.0 0.0 0.0 0.0 0.03 0.16 0.4 0.9 0.1 0.1 0.1 0.1 0.25 0.7 0.99 0.999998 0.0 0.0 0.0 0.0 0.2 0.5 0.7 0.99 0.0 0.0 0.0 0.0 0.01 0.05 0.1 0.2 0.0 0.0 0.0 0.0 1.0E-6 1.0E-6 1.0E-6 1.0E-6 0.1 0.1 0.1 0.1 0.3 0.5 0.47 0.06 0.8 0.8 0.8 0.8 0.7 0.2999 0.009999 1.0E-6 0.1 0.1 0.1 0.1 0.3 0.3 0.2 0.009999 0.0 0.0 0.0 0.0 0.09 0.15 0.3 0.2 0.0 0.0 0.0 0.0 1.0E-6 1.0E-6 1.0E-6 1.0E-6 0.8 0.8 0.8 0.8 0.6 0.3 0.1 0.02 0.1 0.1 0.1 0.1 0.05 1.0E-4 1.0E-6 1.0E-6 0.9 0.9 0.9 0.9 0.5 0.2 0.1 1.0E-6 0.0 0.0 0.0 0.0 0.2 0.3 0.3 0.3 0.0 0.0 0.0 0.0 1.0E-6 1.0E-6 1.0E-6 1.0E-6 0.09 0.09 0.09 0.09 0.06 0.03 0.02 0.01 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 0.7 0.5 0.3 0.3 0.0 0.0 0.0 0.0 1.0E-6 1.0E-6 1.0E-6 1.0E-6 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 0.999996 0.999996 0.999996 0.999996 ); } relation HomeBase RiskAversion SocioEcon { values= table (1.0E-6 0.15 0.35 0.489999 1.0E-6 0.01 0.2 0.95 1.0E-6 0.299999 0.5 0.85 1.0E-6 0.95 0.999997 0.999997 0.8 0.8 0.6 0.5 0.8 0.25 0.4 1.0E-6 0.8 1.0E-6 1.0E-6 1.0E-6 0.8 1.0E-6 1.0E-6 1.0E-6 0.049999 0.04 0.04 1.0E-6 0.05 0.6 0.3 1.0E-6 0.05 0.6 0.4 0.0010 0.05 0.024445 1.0E-6 1.0E-6 0.15 0.01 0.01 0.01 0.149999 0.14 0.1 0.049998 0.149999 0.1 0.099999 0.148999 0.149999 0.025554 1.0E-6 1.0E-6 ); } relation AntiTheft RiskAversion SocioEcon { values= table (1.0E-6 1.0E-6 0.05 0.5 1.0E-6 1.0E-6 0.2 0.5 0.1 0.3 0.9 0.8 0.95 0.999999 0.999999 0.999999 0.999999 0.999999 0.95 0.5 0.999999 0.999999 0.8 0.5 0.9 0.7 0.1 0.2 0.05 1.0E-6 1.0E-6 1.0E-6 ); } relation PropCost OtherCarCost ThisCarCost { values= table (0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.95 0.0 0.0 0.95 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.05 0.98 0.0 0.05 0.4 0.95 0.0 0.98 0.8 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.02 1.0 0.0 0.0 0.05 1.0 0.02 0.2 0.4 1.0 1.0 1.0 1.0 1.0 ); } relation OtherCarCost Accident RuggedAuto { values= table (1.0 1.0 1.0 0.99 0.98 0.95 0.6 0.5 0.4 0.2 0.1 0.0050 0.0 0.0 0.0 0.0050 0.01 0.03 0.2 0.2 0.3 0.4 0.5 0.55 0.0 0.0 0.0 0.00499 0.009985 0.01998 0.19998 0.29997 0.29996 0.39996 0.39994 0.4449 0.0 0.0 0.0 1.0E-5 5.0E-5 2.0E-5 2.0E-5 3.0E-5 4.0E-5 4.0E-5 6.0E-5 1.0E-4 ); } relation OtherCar SocioEcon { values= table (0.5 0.8 0.9 0.95 0.5 0.2 0.1 0.05 ); } relation MedCost Accident Age Cushioning { values= table (1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 0.96 0.98 0.99 0.999 0.96 0.98 0.99 0.999 0.9 0.95 0.97 0.99 0.5 0.8 0.95 0.99 0.5 0.8 0.95 0.99 0.3 0.5 0.9 0.95 0.3 0.5 0.9 0.95 0.3 0.5 0.9 0.95 0.2 0.3 0.6 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.03 0.019 0.0099 9.9E-4 0.03 0.019 0.0099 9.9E-4 0.07 0.04 0.025 0.0070 0.2 0.15 0.02 0.0070 0.2 0.15 0.02 0.0070 0.3 0.2 0.07 0.03 0.3 0.2 0.07 0.03 0.3 0.2 0.07 0.03 0.2 0.3 0.3 0.05 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0090 9.0E-4 9.0E-5 9.0E-6 0.0090 9.0E-4 9.0E-5 9.0E-6 0.02 0.0070 0.0030 0.0020 0.2 0.03 0.02 0.0020 0.2 0.03 0.02 0.0020 0.2 0.2 0.02 0.01 0.2 0.2 0.02 0.01 0.2 0.2 0.02 0.01 0.3 0.2 0.07 0.03 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0010 1.0E-4 1.0E-5 1.0E-6 0.0010 1.0E-4 1.0E-5 1.0E-6 0.01 0.0030 0.0020 0.0010 0.1 0.02 0.01 0.0010 0.1 0.02 0.01 0.0010 0.2 0.1 0.01 0.01 0.2 0.1 0.01 0.01 0.2 0.1 0.01 0.01 0.3 0.2 0.03 0.02 ); } relation Cushioning RuggedAuto Airbag { values= table (0.5 0.7 0.0 0.1 0.0 0.0 0.3 0.3 0.1 0.6 0.0 0.0 0.2 0.0 0.6 0.3 0.0 0.7 0.0 0.0 0.3 0.0 1.0 0.3 ); } relation Airbag MakeModel VehicleYear { values= table (1.0 0.1 1.0 0.05 1.0 0.2 1.0 0.6 1.0 0.1 0.0 0.9 0.0 0.95 0.0 0.8 0.0 0.4 0.0 0.9 ); } relation ILiCost Accident { values= table (1.0 0.999 0.9 0.8 0.0 9.98E-4 0.05 0.1 0.0 1.0E-6 0.03 0.06 0.0 1.0E-6 0.02 0.04 ); } relation DrivHist DrivingSkill RiskAversion { values= table (0.0010 0.0020 0.03 0.3 0.1 0.5 0.9 0.95 0.3 0.6 0.99 0.999998 0.0040 0.0080 0.15 0.3 0.3 0.3 0.07 0.04 0.3 0.3 0.009999 1.0E-6 0.995 0.99 0.82 0.4 0.6 0.2 0.03 0.01 0.4 0.1 1.0E-6 1.0E-6 ); } }