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Genetic Algorithms
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Luke Williams
July 16, 2020
Science
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Genetic Algorithms
Solving problems the natural way
Luke Williams
July 16, 2020
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Transcript
Genetic Algorithms Solving problems the natural way
Making Decisions - go to the market?
Making decisions - which car to buy?
Making decisions - mimic art? wizardry! 50 semi transparent shapes
Mona Lisa
Designing a car by mistake
Under the hood Candidates Genome Fitness List of candidate solutions
to the problem. “Genetic” code for each candidate that describes the characteristics that will “evolve” How to determine the “fittest” candidates
Under the hood Candidates Genome Fitness 14aF2bdz12 9avg2bc1sd 44bg92jcks 120m
90m 1m
Under the hood 14aF2bdz12 shape wheel size wheel position wheel
density chasis density
Under the hood Candidates Genome Fitness 14aF2bdz12 14aG2bdz12 25aF2cdz12 ?
? ?
Under the hood Candidates Genome Fitness 14aF2bdz12 14aF2bc1td ? ?
? 9avg2bc1sd
Under the hood Clone/mate to build the next generation Find
the fittest candidate(s) Randomly mutate the genome Build all candidates in generation
In the wild
In the wild
In the wild - Flight / train scheduling - Timetabling
- e.g at a school - Factory floor design - Mechanical engineering - Music production - Financial modelling - Code-breaking - Artificial Intelligence
Genetic Algorithms Solving problems the natural way