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# 05-midterm - CS570 Midterm Exam Name Question Your Points 1...

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CS570 Midterm Exam March 25, 2009 Name: Question Your Points Points 1 17 2 14 3 6 4 6 5 4 6 15 7 8 8 15 Total 85 1

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1 True/False (17 points) For each of the following statements, answer True or False. Also, add a short explanation of your answer. An answer without any explanation will get zero points. A. (3 points) Best-first search is a greedier algorithm than A* search. Thus, it may find sub-optimal solutions, but by expanding nodes closer to the goal sooner, it is guaranteed to find a goal sooner (after an equal or fewer number of node expansions) than A*. [True / False] B. (3 points) Let h 1 and h 2 be two admissible heuristic functions. Then, max ( h 1 , 0 . 5 * h 2 ) is also admissible. [True / False] C. Suppose you have a CSP problem, and you run arc consistency starting from the initial state (before any variables are assigned). After apply- ing arc consistency, all variables have one or more possible value, and there is a variable V i whose domain D i has exactly one possible value remaining ( | D i | = 1). (a) (2 points) There must be at least one solution to this CSP problem. [True / False] 2
(b) (2 points) Any solution to this CSP problem must have the vari- able V i instantiated to the value in D i . [True / False] D. The standard alpha-beta pruning performs a depth-first exploration (to a specified depth) of the game tree. (a) (2 points) Alpha-beta pruning can be generalized to do a breadth- first exploration of the game tree and still get the optimal answer. [True / False] (b) (2 points) Alpha-beta pruning can be generalized to do an iterative- deepening exploration of the game tree and still get the optimal answer. [True / False] E. (3 points) Suppose you have an MDP, where the reward is 0 per step until the robot gets to a goal (but not terminal) state, and the reward is 1 from then on (the rewards keep accumulating). Also γ < 1. Suppose that you have two policies π 1 and π 2 , both of which are guaranteed to get your robot to the goal. Also, suppose that starting from any state s , the expected (i.e., average) number of steps that π 1 takes to get to the goal is less than the expected number of steps that π 2

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