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In the Wumpus world, A breeze or not in each visited square and no pit in any visited square are abbreviated as b & known:b = ¬b1,1∧b1,2∧b2,1known = ¬p1,1∧¬p1,2∧¬p2,1
what's the probability of a pit at [1,3], given the evidence so far (P(P1,3|known, b))? (Find the most simplified expression.)
When we know the actual values of the following probabilities, how can we calculate P(¬b|a)? (Make sure that you can get an actual value, not just an equation. This calculation may require two or three steps.)
•P(a)
•P(b)
•P(a|b)
•P(a|¬b)
In the Wumpus world, A breeze or not in each visited square and no pit in any visited square are abbreviated as b & known:b = ¬b1,1∧b1,2∧b2,1known = ¬p1,1∧¬p1,2∧¬p2,1
what's the probability of a pit at [1,3], given the evidence so far (P(P1,3|known, b))? (Find the most simplified expression.)
How to calculate the value of P(cavity ∨ toothache) based on the following the full joint distribution?
How to calculate the value of P(cavity | toothache) = P(cavity ∧ toothache) / P(toothache) based on the following full joint distribution?
What axiom shows the product rule form?
There are two random variables: Weather and Cavity.Each random variable has the following values:Weather = {sunny, rain, cloudy, snow}Cavity = {cavity, ¬cavity}
What is the conditional probability of having rain given that there is a cavity?
Which equation shows Bayes' Rule?
We have four random variables: Weather, Toothache, Catch, Cavity. But we know that dental problems don't influence the weather. And we know that the weather doesn't seem to influence dental variables.
Which is expressed correctly based on these facts?
What will be the result after applying the resolution inference rule to the following?