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Recipe: AILearnsToPlayFoldItZW
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Name: AILearnsToPlayFoldItZW
ID: 103349
Created on: Sat, 03/28/2020 - 23:01
Updated on: Sun, 03/29/2020 - 06:03
Description:

version 1.01 It is a script that use genetic algorithm to find actions in game that gain score and adjust them over time. Source code can be found here: https://github.com/Grommii/Foldit/blob/master/AILearnsToPlayFoldIt.lua

Adjustable parameters: **Population Size** - Number of species in population. In other words - number of top species that survive to the next generation; **Mutation Size** - Number of mutated algorithms that will be added and checked each generation; **Aliens Size** - Number of random algorithms that will be added and checked each generation; **Cross Size** - Number of crossed algorithms that will be added and checked each generation; **Number Of Algorithm Steps** - Number of actions (genes) that can perform each algorithm; **Iteration Score Threshold** - Score gain threshold for algorithm to be executed again during evaluation; **Reset World Generation Each** - Number of generations that will be tested based on the same starting position before new top position will be saved as start point; **Mutate Rate** - Probability of new gene during mutation;

Also you can check/uncheck pre-defined algorithms to start with. By default two common algorithms included.



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Joined: 03/31/2020
Groups: None
Hashes found with 8 iterations which may be of further use

164A8315539483960529
51415126016041500A2A

These may be of use in other proteins, but I found these in the "staphylococcus protein electron density" puzzle for 69 seconds of folding per algorithm. Maybe there could be a random function that may include/involve pre-generated hashes?

Also, may I recommend time management as a part of the algorithm?

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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons