Peer review to Lab 9/lab9ipynb

[PaolaMts]

Hi, I'm here to review your code. Here are some of my thoughts on it:

• The use of dataclasses to represent individuals simplifies the management of information associated with each individual and make the system modular and easy to understand.
• Tracking the performance of the bit mutation through the __better_with_0_1 list and dynamically adapting the probability are positive aspects for improving the algorithm during execution.
• A small suggestion: you could have added a condition to halt the algorithm once the fitness reaches 100%, avoiding unnecessary iterations

Considering all this, I think your code is well-structured and achieves good results, although it may not find a solution for all problem dimensions

[anubis09]

We didn't implement a condition to halt the fitness function once it reached 100% because we assumed to not know the maximum value of the fitness function. Anyway, thank you for your feedback