M= M= Low High 0.5 0.5 E = E= Good Bad Mileage Mileage Engine AC = AC = Working Broken Air Conditioner Low Car Value High Engine Air CV= CV= Conditioning Low High Good Working Good Broken Bad Working Bad Broken 4.2) Use the Bayesian network to determine the probability of the engine being of good condition, given the mileage is low, the car's value is low but the air conditioner is in working order. Show all your calculations.

M= M= Low High 0.5 0.5 E = E= Good Bad Mileage Mileage Engine AC = AC = Working Broken Air Conditioner Low Car Value High Engine Air CV= CV= Conditioning Low High Good Working Good Broken Bad Working Bad Broken 4.2) Use the Bayesian network to determine the probability of the engine being of good condition, given the mileage is low, the car's value is low but the air conditioner is in working order. Show all your calculations.

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter12: Review Of Calculus And Probability

Section: Chapter Questions

Problem 7RP

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Suppose we use the following KB (where x, y, z are variables and r1, r2, r3, goal are constants) to determine whether a particular robot can score. (a) Open(x) ∧ HasBall(x) → CanScore(x)(b) Open(x) ∧ CanAssist(y, x) ∧ HasBall(y) → CanScore(x) (c) PathClear(x,y) → CanAsist(x,y)(d) PathClear(x,z) ∧ CanAssist(z,y) → CanAssist(x,y) (e) PathClear(x,goal) → Open(x)(f) PathClear(y,x) → PathClear(x,y) (g) HasBall(r3)(h) PathClear(r1,goal) (i) PathClear(r2,r1) (j) PathClear(r3,r2) (k) PathClear(r3,goal) Intuitively, CanScore(x) means x can score on goal. CanAssist(x, y) means there exists some series of passes that can get the ball from x to y. Open(x) means x can shoot on goal directly. And P athClear(x, y) means the path between x and y is clear. Provide a SLD-derivation for the query CanScore(x) in which the answer provided is r1. Provide a SLD-derivation for the query CanScore(x) in which the answer provided is r3. How many “distinct” derivations (i.e., involving different…
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