Lecture 12 and 13

Today’s topic: P vs NP

This will be a not so formal introduction to P and NP. Every computer scientist should know something about NP complete problems. If you know that a problem is NP complete, then you know that it is very hard to find an optimal solution.

  • The definition of P and NP
  • The definition of Reduction and NP Hardness
  • NP Completeness
  • Some NP Complete Problems.
  • What now? What courses should I take to learn more about algorithms and optimisation?

These lectures will given by Pierre Flener.

The slides for the lecture can be found here

Reading Guide

What should I know by the end of this set of lecture?

  • The definition of NP? What has guessing a solution got to do with complexity?
  • How do reductions work?
  • What is a complete problem for a complexity class?
  • You should know some NP-complete problems and have enough idea about how reductions work so that you can decide if your problem is NP-complete or not.
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