9.3: Genetic Algorithm: Shakespeare Monkey Example - The Nature of Code
Part 3 of the Genetic Algorithm series is dedicated to the Shakespeare Monkey Example. In this video, I use the evolutionary concepts from the previous video to compute a problem that a brute force algorithm wouldn't be able to solve. https://thecodingtrain.com/more/archive/nature-of-code/9-genetic-algorithms/9.3-shakespeare-monkey-example.html
๐น๏ธ p5.js Web Editor Sketch: https://editor.p5js.org/codingtrain/sketches/GUZKUFxKo
๐ฅ Previous video: https://youtu.be/RxTfc4JLYKs?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
๐ฅ Next video: https://youtu.be/-jv3CgDN9sc?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
๐ฅ All videos: https://www.youtube.com/playlist?list=RxTfc4JLYKs&list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
Links discussed in this video:
๐ Nature of Code Book: https://natureofcode.com/
๐ Shakespeare Monkey Theorem: https://en.wikipedia.org/wiki/Infinite_monkey_theorem
Timestamps:
0:00 Hello!
0:53 Exploring the interface of this sketch.
2:16 How about unicorn?
2:42 Let's change the mutation rate to be 0.
3:28 What play around with the population?
6:36 Is a larger mutation rate better?
7:24 What's next?
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