Front-Loaded Evolution via Genetic/ Evolutionary Algorithms- What gets Front-Loaded"?
In Genetic/ Evolutionary Algorithms and My Front-Loaded Evolution I stated the case for front-loaded evolution via genetic/ evolutionary algorithms.
Today I will expand on that by telling you what gets front-loaded- well I will be telling those who are not up to the task of putting that together from what I had posted in that blog:
So with my idea of front-loaded evolution we would have the initial conditions, the required resources, the specified result (ie what you are trying to accomplish) and then the algorithms to make it all happen.
So what gets front-loaded?
1- You need a target-> the goal-> what it is you are trying to achieve. No need to write an algorithm if there isn't a problem to solve-
"I wrote an algorithm"
"What does it do?"
"It's an algorithm, stupid."
"How do you know when its done?"
So the specifications of what you are trying to achieve are front-loaded. As the algorithm chugs along it keeps checking for any match to those specs.
2- You need to figure out a valid starting point- those initial conditions- one way is to determine what it is minimal you can do, without any algorithm, to get as close to the target.
The initial condition(s) is(are) front-loaded
3- You need the proper resources that the algorithm can use to get from starting point to the target.
Those resources are front-loaded.
4- Then there is that algorithm or algorithms that, from the initial conditions and the provided resources, some of which can be by-products of the algorthim(s), can produce the desired solution.
The algorithm(s) is(are) front-loaded.
That should be it- once you do all of that and hit "go" it is hand's off for the designer(s).
What did Dawkins do for "weasel"- He had a specified sentence in mind. He set the initial conditions as a sequence of letters. He had the resource of the alphabet to call upon and then wrote an algorithm that would make it so.