Hi, I hope this question is appropriate on here, I’m a new user after searching for usable AI forums. I’m really new to AI implementations, and recently started experimenting with genetic algorithms (finding the optimal solutions), and afterwards now started looking at genetic programming (finding the optimal program for solutions). The mutation, crossover etc. on decision trees are relatively straight forward to me, but am still struggling to wrap my head around the implementation of problems.

So, a genetic program can find the math function for a set of correlating inputs values to outputs. If you then the optimization problem (let’s say bin packing problem), how can you use a genetic program to determine the most optimal objective function / fitness function for the problem? Then you will be able to use that generated fitness function for implementation on the GA to find the optimal solution to the problem?

If I understand this correctly, how will the GP process be feasible? Is it some general used technique, is the approach related to landscape evaluation for optimization problems… or? Any help will be greatly appreciated. I know there’s a solution, just don’t know where / how to search for it, or what it’s referred to…

Thank you in advance.