Evolve schema directly using instruction matrix based genetic programming

This paper proposes a new architecture for tree-based genetic programming to evolve schema directly. It uses fixed length hs-expressions to represent program trees, keeps schema information in an instruction matrix, and extracts individuals from it. In order to manipulate the instruction matrix and the hs-expression, new genetic operators and new matrix functions are developed. The experimental results verify that its results are better than those of the canonical genetic programming on the problems tested in this paper.