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*To*: Rao Kambhampati <rao@asu.edu>*Subject*: Exam specimen questions..*From*: Subbarao Kambhampati <rao@asu.edu>*Date*: Wed, 1 Feb 2012 07:25:05 -0700*Dkim-signature*: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=gamma; h=mime-version:sender:from:date:x-google-sender-auth:message-id :subject:to:content-type; bh=9KtwueHOKoovYH0n69wdmd/Akt9LdN0FhPDPWaKCujE=; b=cYVbbTGrcrPPdIu0tZfNpFBg2SqDhfnjCnoePumo3X6fEcIzVVe7OEjGgeQFpipbsT vALhygHJQy2EbkOeh1DPIzqiexzJEQgGddJ7GH/kiliis4ZFbK7m5RgLXKV8b0QeZcWI ubCp4Rk3ZV2r+uBmo+32vBtaFZt3TeoxNSMpw=*Sender*: subbarao2z2@gmail.com

Folks

You may want to note that Qn 11 on the homework, i.e., the one at http://rakaposhi.eas.asu.edu/cse471/hw2-f06-qn3-4.pdf

is directly from a previous midterm. So it gives you an idea of how the exam questions will look like

Also, I might ask True/False *with explanation* short answer questions such as the ones below:

For each of the following statements below, indicate whether the statement is true or false, and give a brief but precise justification for your answer. Correct answers *with correct justifications* will carry 2points. No points will be awarded for answers without correct justifications. Example qn: The time and memory requirements of IDA* can be improved by using A* algorithm to do search in individual iterations. Answer: False. Because A* in the worst case can take as much memory as breadth-first, and thus using A* in the individual iterations will make IDA* require exponential memory (instead of linear memory). A. A* search does b^(d/2) node expansions when searching a unifrom tree of branching factor b and depth d, using a perfect heuristic. B. Consider a uniform search tree of depth d and branching factor b, where there are many goal nodes, all of which are uniformly distributed at the leaf level d. Assuming that memory consumption is not a problem, we are better off using breadth-first search than depth-first search in this scenario. C. A* search with heuristic h=0 will always have to search the entire tree before finding the optimal solution. D. Suppose A* search uses an evaluation function f(n) = (1-w) g(n) + w h(n). For any value of w between 0 and 1 (inclusive), A* will terminate and return optimal solution. E. If h1 and h2 are two admissible heuristics, and h3 is defined as h3(n) = max(h1(n) , h2(n)) , then A* search with h3 is guaranteed to return an optimal solution while expanding as many or fewer nodes than either h1 or h2.

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