ProcJam-2018

ProcJam 2018 Entry. Simulate basic population genetics on fake creatures' DNA. Concepts of mutation, crossover, fitness distribution covered.

Try it Out Here - https://barrettotte.github.io/ProcJam-2018/WebGL/index.html

Links

• Short video - https://youtu.be/aZF-uBzwVLA
• Procedural Generation Jam 2018 - https://itch.io/jam/procjam
• WebGL Build - Try it Out Here - https://barrettotte.github.io/ProcJam-2018/WebGL/index.html
• Procedural Generation Jam 2018 Entry Itch.io Page - https://barrettotte.itch.io/simple-population-genetics-simulator
• This idea was prototyped in Python first, https://github.com/barrettotte/Population-Genetics-Sim

Summary

• This script will simulate a generation of "creatures" generation after generation until the ideal color allele is found.
• Each creature has one allele in their "DNA" for color and is passed to offspring based on fundamentals of genetics (crossover, mutation).
• Depending on how close the creature's color allele is to the ideal allele, it is given a fitness value which affects its chances of reproducing with another creature.

Screenshots

Process

• Initialize - Population N random DNA
• Selection - Evaluate fitness, generate mating pool
• Reproduction - Repeat N times, pick parents based on "weighted random" of mating rate
• Crossover - Combine DNA through some crossover method
• Mutation - Mutate child based on mutation rate
• Add child to new generation
• Discard old population
• Repeat

Additional Process

• A percentage of "Top" fitness organisms will asexually reproduce to keep their ideal DNA in the mating pool.
• There is a small chance a random organism will asexually reproduce

Sources:

• Basics of bitwise crossover/mutation http://www.obitko.com/tutorials/genetic-algorithms/crossover-mutation.php
• Noun and Adjective Lists https://github.com/aaronbassett/Pass-phrase