I recently graduated with my Master's in Computer Science. I spent a majority of my graduate career working as a graduate research assistant under a professor of mine who specialized in genetic algorithms. My university doesn't offer a PhD program, so my plan for this summer was to continue collaborating on research with him until I could get into a PhD program elsewhere. However, this past winter semester Dr. Horn unfortunately passed away. He was the only professor at my university who specialized in his field, so I don't have much in the way of academic references anymore. In order to get into a program, I'm thinking my best bet is to get something published so that I can at least build up my CV. That is obviously going to take time though, and I'd like to start paying off my student loans as soon as possible. Any advice on finding a job using my experience with genetic algorithms?

How to use binary two-point crossover in Genetic Algorithm using R. Like- Single Point Crossover gabin_spCrossover(object,parent,...)

Uniform Crossover gabin_uCrossover(object,parent,...)

Suggest anyother binary crossovers also

GitHub Repository: https://github.com/ahmedfgad/GeneticAlgorithmPython

Documentation: https://pygad.readthedocs.io/en/latest

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PyGAD is a Python library for solving optimization problems using the genetic algorithm. It supports deterministic/indeterministic single/multi-objective optimization and training Keras and PyTorch models.

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Release Quick Summary:

1. Support of multi-objective optimization using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) using the NSGA2 class in the pygad.utils.nsga2 module.

2. Two new NSGA-II parent selection methods are supported in the pygad.utils.parent_selection module: 1) Tournament selection for NSGA-II 2) NSGA-II selection.

3. A new instance attribute named pareto_fronts added to the pygad.GA instances that holds the pareto fronts when solving a multi-objective problem.

4. The plot_fitness() method in the pygad.plot module has a new optional parameter named label to accept the label of the plots.

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Check this link for the full release notes: https://pygad.readthedocs.io/en/latest/releases.html#pygad-3-2-0

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For donation:

- Credit/Debit Card: https://donate.stripe.com/eVa5kO866elKgM0144

- Open Collective: opencollective.com/pygad

- PayPal: Use either this link: paypal.me/ahmedfgad or the e-mail address ahmed.f.gad@gmail.com

- Interac e-Transfer: Use e-mail address ahmed.f.gad@gmail.com

This summer I am looking to work on a challenging project. What I want to do is use python to create a snake game AI that uses a neural network that is trained by a genetic algorithm to play the snake game in an efficient and impressive way. Please let me know of any videos, websites, and other resources you think may be helpful. I also am wondering how challenging this project will be? I am currently a second year computer science student with some understanding of discrete math, algorithms, and programming (mainly java). Any help or advice is greatly appreciated!

A buddy and I recently launched some open source project. We created a framework in Java with which you can implement a Machine Learning Algorithm. It uses a genetic Algorithm to train a population of Neural Networks based on fitness function. Our motivation was to bring Machine Learning closer to people who only learned Java in school/University and wanna try out Machine Learning without the need of first learning python or super complex Java libraries. It's designed to be easy to use and to be played around with. The gentic Algorithm takes a big part in keeping the Framework as simple as possible.

We put a lot of effort in separating the Genetic Algorithm used in this framework from the rest of our work. It can therefore be used completely without the Neural Networks as well and is fully generic. (Even tho it's much more fun with Neural Networks :D). You can decide which Selection, Mutation or Recombination you want to use and even implement our own Selection/Mutation/Recombination process. (The most known ones are already implemented though)

Here is a tutorial how to predict diabetes with this framework: https://easy-ml.gitbook.io/easy-ml-for-java/fundamentals/implement-your-first-ai

Please also look at the GitHub repository and leave some feedback about code and design. (Especially considering the ReadMe)
https://github.com/tomLamprecht/Easy-ML-For-Java

Thanks so much!

PS: we earn no cent with this project, and we just do it for the experience. So feedback is basically our payment :D (We also take GitHu Stars tho lol)

Thank you guys so much!

Good news: The submission deadline of EvoMUSART 2023 has been extended to November 16th! 🙌

You still have time to submit your work to the 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART).

If you work with Artificial Intelligence techniques applied to visual art, music, sound synthesis, architecture, video, poetry, design or other creative tasks, don't miss the opportunity to submit your work to EvoMUSART.

EvoMUSART 2023 will be held in Brno, Czech Republic, between 12 and 14 April 2023. 🇨🇿

For more information, visit the conference webpage: https://www.evostar.org/2023/evomusart/

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https://preview.redd.it/5kgjbl6t2ux91.png?width=2083&format=png&auto=webp&s=73a80f2db8efd56ba2dd51321e0c8196a9147789

Hello colleagues,

We are organizing the 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) and we think it may be of interest to many of you. The conference will take place in Brno, Czech Republic, between 12 and 14 April 2023.

If you work with Artificial Intelligence techniques applied to visual art, music, sound synthesis, architecture, video, poetry, design or other creative tasks, you can present your work at this conference.

If not, it is also a great opportunity to know all the news of research in these fields.

For more information, visit the event's webpage: https://www.evostar.org/2023/evomusart/

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https://preview.redd.it/y4qbkaby20p91.png?width=4167&format=png&auto=webp&s=1c44ab51b8cce6a8a4f9edb25596529052084715

Suppose we have different working components...how can I use a genetic algorithm for arranging them and making the optimal mechanism for a particular task?

I'm trying to use the genetic algorithm to maximize accuracy and recall. However, I only have an implementation where one of them can be maximized; any modifications that can be made? I imagine I could do this with a few if/else statements, choosing to produce children of the top parents that have the best fitness for my desired characteristic, but I was wondering if there was a more... rigorous way to go about this.

Thanks!

Hello, I have a multi objective optimization problem that is to be solved using genetic algorithm. The following is one of the objective function

w= (h3-h4)/(h2-h1)

There are 4 independent variables. Can we just optimize only 2 variables like h2 and h3 ? Also can we use string variables as optimization variables ?