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SUMMARY:Genetic Algorithms - Will Hayter-Dalgliesh\, Magdalene College
DTSTART:20210303T193000Z
DTEND:20210303T200000Z
UID:TALK157957@talks.cam.ac.uk
CONTACT:Matthew Ireland
DESCRIPTION:Many problems in computer science can be solved in polynomial 
 time meaning we can get solutions almost instantly (or at least after a fe
 w minutes). However\, there is a large set of problems that are NP-Hard an
 d could potentially take a lifetime to solve through thoroughly searching 
 the solution space. To approximate an optimal solution in a reasonable amo
 unt of time\, we utilise the very versatile genetic algorithm model. In th
 is talk\, I will walk through the full process of applying the genetic alg
 orithm to a problem by using the 0-1 knapsack problem as an example. We wi
 ll see how mimicking survival of the fittest and natural reproduction can 
 help us converge from a population of possible solutions to a single optim
 al solution.\n\nWhile I currently still intend to talk a bit about real wo
 rld implementations of the GA\, I'm not sure if I will have the time to fu
 lly flesh that section out\, so I left it out of my initial abstract draft
  as I don't want to promise something that I may not be able to fully deli
 ver.
LOCATION:Online\, via MS Teams
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