13_Revision - Wednesday 08/09/10 Dr. Daniel Hughes...

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CSC 30155 Wednesday 08/09/10 Dr. Daniel Hughes daniel.hughes@xjtlu.edu.cn
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This Lecture l Information on the Exam (5 mins) l Greedy Algorithms (15 mins) l Dynamic Programming (15 mins) l String Algorithms (15 mins) l Feedback (5 mins)
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The Midterm Exam - Where to go: - Tuesday 26th October - 10:00AM - 11:30AM - Room 137, Building 1 - Duration = 1.5 hours. - You need to bring: - Your ID card. - Pen, pencil, eraser. - Casio FX82ES/83ES calculator.
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Exam Format l You will be asked to answer 2 questions from of 3 . If you answer more than this, I will only count the 2 questions on which you scored highest. l You should make sure you have answered two questions as well as possible before attempting a third. l You have between 30 and 45 minutes per question.
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General Tips l Read the question carefully . People lose marks every year due to answering a different question than what was asked. l Explain your answers in detail . This gives me more opportunities to award you marks. l Use all of the exam time . Even if you feel confident, you can spend time checking your answers.
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These Revision Slides l Pay attention , these slides contain tips on where to focus, but I will not tell you explicitly. l Ask questions , make sure you understand what is expected of you. l Use the exam materials . If you can answer all of those questions well, you will do very well in the exam.
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Final Note l I will be away tomorrow and Monday at a conference. l I will try to respond to emails if you have urgent queries.
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Any Questions?
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CSC 30155 Greedy Algorithms Dr. Daniel Hughes daniel.hughes@xjtlu.edu.cn
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Greedy Algorithms l In the context of algorithms, a greedy algorithm always makes the locally optimal choice (at each stage). l It does not consider past performance. l It does not consider future performance. l This strategy will succeed where successive greedy ‘local’ choices result in a ‘globally’ optimal result. l This only works if a local decision rule exists that can construct an optimal solution for a problem. l As you might expect there are only a small number of optimal greedy algorithms.
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When are Recursive Greedy Algorithms Optimal? l A simple recursive greedy algorithm produces an optimal answer if the following properties are true: l The Greedy Choice Property : For every instance, there is an optimal solution consistent with the first greedy choice. l The Recursive Property : For every instance S of the problem there is a smaller instance S` such that, using any optimal solution to S` , one obtains a best-possible solution for S .
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Greedy Activity Selection l We will look at a problem for which there is a known optimal greedy solution. l Each activity ( A ) is defined by a start time ( A.s ) and a finish time ( A.f ). These are non-negative numbers and (
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13_Revision - Wednesday 08/09/10 Dr. Daniel Hughes...

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