Ahh yes it is tommorrow

Okay, so assuming the first program works well, I will naturally want to make it better

What I have made with the little 'neurons' communicating will now come in handy. They are very flexible objects, they can make connections based on their own logic, and if the first project works, it will be able to do this really well for one game.

Now, what if I wanted my program to learn 2 different games?

The second step of this project will be to allow the program to learn 2 games, by re-using some of the same neurons!! This is something that to my understanding is something a genetic algorithm cant do. Can one genetic algorithm learn to play different games, yes, but they cant do it with the same gene! (again, to my understanding).

There is a challenge to this, all input is different for each game, and these neurons are only set in to take a specific input. The problem is, how does it assign variables to spots that are missing? Well, the program is going to need to mutate to find this out (for now). It will be able to call on a neuron that uses a different game's logic, and will assign it variables randomly. Further progressions would be to have a logic for assigning these variables.... how I am not sure yet but I do already have a few ideas.... which I will write about another time...

okay updates WILL come more frequently!!!

For the past few days I have been contemplating what my little program may be able to do, and how to improve it.

Here's the game plan
The first program I will write, will be able use logic and math combined to have a final outcome. The logic will be solid once the mutated being is created, this is not to say that it will react the same way in a given situation (as it may consider a random variable), but that it will always consider the same variables.

This program may be capable of creating logic in a algorithm differently than any way I have researched. There are different 'neurons' each with their own set of logic that is set to take in certain input, either from other 'neurons' or the input given. (all input is in form of numbers). This may allow a few neurons to concentrate on what strategy is best, it may also condense information to a more usable form before the initial processing. the condensing of information will allow faster processing, however the only way for me to ensure that this can happen is if i not only select which algorithms are best on the ability to solve the problem, but also its efficiency. Efficiency of algorithms does not seem to come in play in other methods of genetic algorithms, as they always have the same efficiency the way it is set up.

Tommorow... What I want the next program to be able to develope to.... much closer to something may be able to think like us...

I would like anybody reading this to keep in mind I am being very theoretical here-- really more like experimental with what the actual capabilities of the program will be. I am assuming if I give the program near infinite flexibility, as well as the ability to be selected on efficiency, it will evolve into something that can effectively solve multiple problems, just like we came about. If nothing else this will be fun, after all I am very young :-)