### Node Trav
* P(Trav) = 0.05
* P(¬Trav) = 0.95
### Node OC
* P(OC) = 0.8
* P(¬OC) = 0.2
### Node Fraud
* P(Fraud | Trav) = 0.01
* P(Fraud | ¬Trav) = 0.004
* P(¬Fraud | Trav) = 0.99
* P(¬Fraud | ¬Trav) = 0.996
### Node CRP
* P(CRP | OC) = 0.1
* P(CRP | ¬ OC) = 0.01
* P(¬CRP | OC) = 0.9
* P(¬CRP | ¬ OC) = 0.99
### Node FP
* P(FP| Trav, Fraud) = 0.9
* P(FP| Trav, ¬Fraud) = 0.9
* P(FP| ¬Trav, Fraud) = 0.1
* P(FP| ¬Trav, ¬Fraud) = 0.01
* P(¬FP| Trav, Fraud) = 0.1
* P(¬FP| Trav, ¬Fraud) = 0.1
* P(¬FP| ¬Trav, Fraud) = 0.9
* P(¬FP| ¬Trav, ¬Fraud) = 0.99
### Node IP
* P(IP| OC, Fraud) = 0.15
* P(IP | OC, ¬Fraud) = 0.1
* P(IP | ¬ OC, Fraud) = 0.051
* P(IP | ¬ OC, ¬Fraud) = 0.001
* P(¬IP | OC, Fraud) = 0.85
* P(¬IP | OC, ¬Fraud) = 0.9
* P(¬IP | ¬ OC, Fraud) = 0.949
* P(¬IP | ¬ OC, ¬Fraud) = 0.999
For a query P(Q|e) where Q is our query variable set and e is the evidence we want to found the corresponding probabilities
- Value Iteration Algorithm