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cs-470fl10:discussion [2014/12/09 15:49] (current)
ryancha created
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 +== Note from TA on errors from Uninformed Search Homework ==
 +On problem 3.17, it is important to note that the number of iterations is a function of the optimal cost, C*, not just on the depth of the solution in the tree.
  
 +Note from Mike: I don't really care if you have the complexity exactly right on this problem, but I do want you to understand the relationship between the optimal cost and the exponential worst-case performance of the algorithm.
 +
 +== PRM Homework Questions (3.7 a,b) ==
 +<u> Question from student </u>
 +If (x,y) is in R^2, there is always going to be an infinite number of potential states. Should I assume that (x,y) is in Z^2 instead? Problem b asks about paths between polygon vertices, which makes sense, but then it asks me to redefine the state space with my answer to the question about the vertices in mind. I guess I just don't see how the question about paths between polygons is related to defining the state space. Since this is supposed to be a homework about probabilistic roadmaps, is the "state space" just the possible positions of some nodes that I would randomly throw in there?
 +
 +<u> Mike's answer </u>
 +Problem 3.7 a is intentionally ambiguous. ​ How many points are there in the plane R^2?  Uncountable. ​ You should conclude that this kind of state space is not compatible with the informed and uninformed searches.
 +
 +Problem 3.7 b wants you to use information about the corners of obstacles to come up with a better state space, one that you define. ​ The hints about obstacle corners is intended to help you define a small, finite state space that is compatible with path planning.
 +
 +== Bayes Homework 2 Question for Problem 2 ==
 +
 +Here is the 2nd problem, with my "muddy points"​ following it (that I just now figured out):
 +
 +----
 +
 +2. Suppose we have three random Variables A, B and C. Suppose that A and C are binary (True/​False) and that B can take on three values (1,2,3). These variables are related in the following Bayesian Network (sorry for the crude arrows):
 +
 +    A
 +   / \
 +  v   v
 +  B   C
 +
 +
 +Suppose also that the following (conditional) probabilities govern:
 +
 +P(A=True)=0.4
 +
 +P(B=1|A=True)=0.6 P(B=2|A=True)=0.1
 +
 +P(B=1|A=False)=0.2 P(B=2|A=False)=0.7
 +
 +P(C=True|A=True)=0.8
 +
 +P(C=True|A=False)=0.9
 +
 +Note that in each case I expect you to be able to figure out the "​missing"​ probability.
 +
 +A) Compute the Joint distribution for A, B and C.
 +
 +Use this table to compute:
 +
 +B) P(A=True|C=True) C) P(B=3|C=False) D) P(A=True|B=2,​C=True)
 +
 +----
 +
 +Muddy points: I am unclear on what the problem is asking me to do. It appears that it has two parts, A and B. At the same time, it seems to be either missing the aforementioned table, or part B ''​is''​ the table. I am inclined to think that a table graphic was intended but not displayed.
 +Another thing that is hard to discern is what the joint distribution should look like. I can tell that sets B and C are both conditional on A, but forming a single table for the Full Joint Distribution has proven confusing. It's easy to make tables for A vs C and A vs B separately, but that doesn'​t do much for me either. I noticed the problem didn't say '''​full'''​ joint distribution. Is there an important distinction in the word "​full"​ here?
 +
 +----
 +
 +Figured out: Looking at the ''​source''​ for the homework wiki page, I could more clearly read and discerned that the problem is indeed separated into parts A and B, as well as C and D. Part A has to be done first, because in it, you are '''​creating'''​ the Joint Distribution table that parts B, C, and D need to compute their answers. I hope that helps others who may have been befuddled by the wiki's inadvertent lack of typesetting.
 +
 +=Kalman Filter Homework 1=
 +The Kalman.h Matlab file near line '''​277'''​ says the following: " Compare this equation to the second equation on page '''​554'''​. ​ Note that the above equation and the equation in the book say the same thing."​ However, there is no equation listed on that page in the current edition of ''​Artificial Intelligence:​ A Modern Approach''​. I think this was referring to another edition of the book. Is the equation on page '''​586'''?​ I see the discrepancy again near line '''​330'''​ and line '''​764'''​.
 +Also, around line '''​389''',​ is the equation supposed to be ''​z = x + sigz^2 * randn(2,​1)''​ ? I would think the x should be a z.
cs-470fl10/discussion.txt ยท Last modified: 2014/12/09 15:49 by ryancha
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