Hard Problems and (Limited) Sloppiness

  • Magnus Lie Hetland


This book is clearly about algorithmic problem solving. Until now, the focus has been on basic principles for algorithm design, as well as examples of important algorithms in many problem domains. Now, I’ll give you a peek at the flip side of algorithmics: hardness. Although it is certainly possible to find efficient algorithms for many important and interesting problems, the sad truth is that most problems are really hard. In fact, most are so hard that there’s little point in even trying to solve them. It then becomes important to recognize hardness, to show that a problem is intractable (or at least very likely so), and to know what alternatives there are to simply throwing your hands up.


Polynomial Time Knapsack Problem Hard Problem Hamilton Cycle Vertex Cover 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© by Magnus Lie Hetland 2010

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  • Magnus Lie Hetland

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