Genetic Programming (GP) is stochastic algorithm, there has been early attempts to explain its convergence with the Schmea Theorem (Holland 1975) for Genetic Algorithm adapted for GP such as (Koza 1992) (O'Reilly 1994) (Altenberg 1994) (Rosca 1997), but I was wondering if someone could point me to the generally agreed theorem that proves GP's covergence? Does it exist?
- [Altenberg 1994]: Altenberg, Lee. "Emergent phenomena in genetic programming." Evolutionary Programming— Proceedings of the Third Annual Conference. World Scientific Publishing, 1994.
- [Goldberg 1989]: Goldberg, David. “Genetic Algorithms in Search, Optimization and Machine Learning.” Addison- Wesley Professional, Reading, MA 1989.
- [Koza 1992]: Koza, John R. Genetic programming: on the programming of computers by means of natural selection.
- [O'reilly 1994]: O'Reilly, Una-May, and Franz Oppacher. Using Building Block Functions to Investigate a Building Block Hypothesis for Genetic. No. 94-04-020. 1994. Vol. 1. MIT press, 1992.
- [Rosca 1997]: Rosca, Justinian P. "Analysis of complexity drift in genetic programming." Genetic Programming (1997): 286-294.