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From: | D X |
Subject: | Re: [Gneuralnetwork] Genetic Algorithm on version 0.6.0 |
Date: | Fri, 25 Mar 2016 22:20:52 -0500 |
Hi JM,
I just finished the new GA search. 1. first hard place is crossover. it is very easy to get an out of ranged value if you use classic bit crossover on double numbers. so I make range [WMIN, WMAX] connected, which means I create a ring which WMIN and WMAX are same point. this way solve the bit crossover out of range issue. 2. suppose each generation we have population SIZE, and each pair of individual will reproduce two new individuals after crossover and mutation. there are SIZE * (SIZE - 1) pairs and plus original SIZE, so the generation pool size should be 2 * SIZE * (SIZE - 1) + SIZE. 3. this GA prefers more generations and less population. when I set more than 100K generations and only 8 population, it still finds a solution. (solution means the error is less than eps, or it cannot get more accurate weight in 100 generations, but it might not be the best solution). 4. the solution found by this GA actually is not as good as the old one, but it is still valuable, because GA is kind of a random search~ attached file is my c and h file, I just added function definition and declaration to the files. I do not have permission to check in code to repo. please review this code, and let me know if you have further thought. Thanks, Github: https://github.com/cxxaddict Nan. From: address@hidden To: address@hidden Date: Fri, 25 Mar 2016 16:06:21 -0500 CC: address@hidden Subject: Re: [Gneuralnetwork] Genetic Algorithm on version 0.6.0 Yes, please let me give it a shot. actually this is my first time to contribute to GNU. Exciting! I will let you know when I am done.(hopefully soon) Thanks, Github: https://github.com/cxxaddict Nan, Date: Fri, 25 Mar 2016 21:34:20 +0100 Subject: Re: [Gneuralnetwork] Genetic Algorithm on version 0.6.0 From: address@hidden To: address@hidden CC: address@hidden; address@hidden Hi Nan, Thanks for this comment! We actually have plans to fix it but if you have any experience with genetic algorithms then you could help us so we go faster. What do you think? Do you feel like you could make a better version everyone could use? Please let us know. Thanks again for this interesting email! JM 2016-03-25 20:49 GMT+01:00 COOL MAN <address@hidden>:
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genetic_algorithm.c
Description: Text document
genetic_algorithm.h
Description: Text document
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