Trees are Complex

Tree structures have nice properties as representations of solutions to many problems. This is rather obvious, but it is also very important- the whole subject of Genetic Programming relies on it. They are used because they can describe things that are built from subexpressions and things that naturally have this structure. But Gene Expression Programming exists essentially as a biologically justified reaction to the complexity of Genetic Programming. In this sense my research is justified in a way I would never have anticipated- it is more like GEP then GEP is. BPGEP is better justified in some ways (though PGEP removed some of the operators that where biologically justified in GEP, but I'm not really concerned about them) and it (hopefully- see my last post) will remove all need to be aware of the tree structure of the solutions.

If we could have a system in which all knowledge of the expression tree is in the evaluator, which included some easy and obvious repair or adjustment operation to ensure all individuals encode some tree or other that works for all problems, then we would have no more reliance on trees and their complex structure. Not that trees are all that complex- the point is that genetic operators work very well for linear symbol lists, especially bit vectors, and GP has historically had much research into finding good operators that respect tree structures. In BPGEP we have a system with a trivial encoding, binary, simple genetic operators (point mutation, single and double point crossovers, and rotation (also selection, but that is not dependent on encoding)), no tree related complexities, and a solid biological justification without going crazy.

I know I posted this idea before, but I want to emphasis that this is a direction consistent with the spirit of the original GEP paper. I feel pretty good about this.