Incremental Approach to Structurally Difficult Problems in Genetic Programming
Keywords:Genetic programming, knowledge discovery, tree data structures
AbstractPaper inspects the reasons for the structural difficulty of genetic representations demonstrated by a well known tunably difficult genetic programming problem. For this type of problem we believe the tree-like structure is not the major cause for problem hardness. Following this we propose a workaround, which is based on simple repetition of the evolution using pre-evolved initial populations and therefore provides closer focus points for evolution. This way the problem is solved using a manageable amount of processing, which was not possible using traditional approach. It also requires no change to the traditional genetic code base compared to other published solutions, which require substantial changes both in encoding and genetic operators. The idea is not bound to structural problems, but can be applied to other problem domains, too.
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