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A Bayesian network has four variables: C,S,R,W, where -- C is independent, with P(C)=0.5 -- S is conditional on C, with P(S|C)=0.1, and P(S|~C)=0.5 -- R is conditional on C, with P(RIC)=0.8, and P(R|~C)=0.2 W is conditional on S and R, with P(W|S,R)=0.99, P(W|S,~R)=0.9, P(W-S,R)=0.9,P(W|~S,~R)=0. a) List possible states of this world. b) Calculate the probability P(RIS).

A Bayesian network has four variables: C,S,R,W, where -- C is independent, with P(C)=0.5 -- S is conditional on C, with P(S|C)=0.1, and P(S|~C)=0.5 -- R is conditional on C, with P(RIC)=0.8, and P(R|~C)=0.2 W is conditional on S and R, with P(W|S,R)=0.99, P(W|S,~R)=0.9, P(W-S,R)=0.9,P(W|~S,~R)=0. a) List possible states of this world. b) Calculate the probability P(RIS).

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A Bayesian network has four variables: C,S,R,W, where -- C is independent, with P(C)=0.5 - S is conditional on C, with P(S|C)=0.1, and P(S|~C)=0.5 -- R is conditional on C, with P(RIC)=0.8, and P(R|~C)=0.2 -- W is conditional on S and R, with P(W|S,R)=0.99, P(W|S,~R)=0.9, P(W|~S,R)=0.9,P(W|~S,~R)=0. a) List possible states of this world. b) Calculate the probability P(RIS).
Transcribed Image Text:A Bayesian network has four variables: C,S,R,W, where -- C is independent, with P(C)=0.5 - S is conditional on C, with P(S|C)=0.1, and P(S|~C)=0.5 -- R is conditional on C, with P(RIC)=0.8, and P(R|~C)=0.2 -- W is conditional on S and R, with P(W|S,R)=0.99, P(W|S,~R)=0.9, P(W|~S,R)=0.9,P(W|~S,~R)=0. a) List possible states of this world. b) Calculate the probability P(RIS).
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