Abstract
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.
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Li, G., Lee, K.H., Leung, K.S. (2005). Evolve Schema Directly Using Instruction Matrix Based Genetic Programming. In: Keijzer, M., Tettamanzi, A., Collet, P., van Hemert, J., Tomassini, M. (eds) Genetic Programming. EuroGP 2005. Lecture Notes in Computer Science, vol 3447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31989-4_24
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DOI: https://doi.org/10.1007/978-3-540-31989-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25436-2
Online ISBN: 978-3-540-31989-4
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