Abstract
Genetic Programming has been slow at realizing other programming paradigms than conventional, deterministic, sequential von-Neumann type algorithms. In this contribution we discuss a new method of execution of programs introduced recently: Algorithmic Chemistries. Therein, register machine instructions are executed in a non–deterministic order, following a probability distribution. Program behavior is thus highly dependent on frequency of instructions and connectivity between registers. Here we demonstrate the performance of GP on evolving solutions to a parity problem in a system of this type.
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Lasarczyk, C.W.G., Banzhaf, W. (2005). An Algorithmic Chemistry for 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_1
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DOI: https://doi.org/10.1007/978-3-540-31989-4_1
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