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📗 (Fall 2018 Midterm Q5) If \(h_{1}\) and \(h_{2}\) are both admissible heuristic functions, which ones of following are also admissible heuristic functions?
📗 Choices:
📗 (Fall 2018 Midterm Q6) Let \(h_{1}\) be an admissible heuristic from a state to the optimal goal, A* search with which ones of the following \(h\) will be admissible?
📗 Choices:
📗 (Fall 2017 Midterm Q10) Let \(h_{1}\) be an admissible heuristic from a state to the optimal goal, A* search with which ones of the following \(h\) will never be admissible?
📗 Choices:
📗 (Fall 2018 Midterm Q9) Let the states be 2D integer points with integer coordinates \(\left(i, j\right)\) with boundary constrains and . Each state \(\left(i, j\right)\) has four successors \(\left(i - 1, j\right), \left(i + 1, j\right), \left(i, j - 1\right), \left(i, j + 1\right)\) or a subset thereof subject to the boundary constraints. The score of state \(\left(i, j\right)\) is . Which local minimum will be reached if hill climbing is used starting from ?
📗 Answer (comma separated vector): .
📗 (Fall 2018 Midterm Q10) In simulated annealing one accepts a transition from \(s\) to an inferior neighbor \(t\) with probability \(\exp\left(\dfrac{- \left| f\left(s\right) - f\left(t\right) \right|}{T}\right)\), where \(T\) is the temperature parameter. Suppose \(f\left(s\right)\) = and \(f\left(t\right)\) = . At what temperature is the transition probability ?
📗 Note: we are minimizing the score.
📗 Answer: .
📗 (Fall 2017 Midterm Q11) In simulated annealing we move from \(s\) to an inferior neighbor \(t\) with probability \(\exp\left(\dfrac{- \left| f\left(s\right) - f\left(t\right) \right|}{T}\right)\), where \(T\) is the temperature parameter. Suppose \(f\left(s\right)\) = and \(f\left(t\right)\) = and \(T\) = . What is the probability we stay at \(s\) instead of moving to \(t\)?
📗 Note: we are minimizing the score.
📗 Answer: .
📗 (Fall 2016 Midterm Q6) Consider the following version of hill climbing: at initial state \(s\) we randomly choose one of \(s\)'s neighbors with equal probability. If the chosen neighbor has a strictly better score than \(s\) we move to the neighbor; otherwise we stay at \(s\). Assume \(s\) has neighbors, and only of the neighbors has a strictly better score than \(s\). What is the chance that we move out of \(s\) in iterations or less?
📗 Answer: .
📗 (Spring 2017 Midterm Q2) Individuals (i.e. candidate solutions) in the current generation are given by -digit sequences: = , , , . The fitness function is . What is the result of performing 1-point crossover for the sequences with the highest fitness (break ties by preferring the sequence that appears earlier in the list) with a cross-point between digit and digit .
📗 Note: the first line representing the first child should start with the sequence with the highest fitness, and the second line representing the second child should start with the sequence with the second highest fitness.
📗 In case you need a calculator: .
📗 Answer (matrix with 2 lines, each line is a comma separated vector): .
📗 Go to the Genetic Car demo Link and experiment with different mutation rates and sizes. You can try different gravity too. Use "View top replay" to pause the simulation, and "Surprise!" and/or "Fast Forward" to speed up the simulation. Post a screen shot of the winner on Piazza.
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📗 Answer: .
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