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In this paper, Genetic Network Programming-Sarsa Learning (GNP-Sarsa) used for creating trading rules on stock markets is enhanced by adding plural subroutines. Subroutine node — a new kind of node which works like ADF (Automatically Defined Function) in Genetic Programming (GP) has been proved to have positive effects on the stock-trading model using GNP-Sarsa. In the proposed method, not only one...
The purpose of this paper is to study how to improve the evolution of GNP-Sarsa with subroutines and its application to trading rules on stock markets. Recently, a successful study, namely GNP-Sarsa, shows us its effectiveness and powerfulness, which combines sophisticated diversified search ability for structures using evolution and intensified search ability of RL for many technical indices and...
The purpose of this paper is to enhance the performance of Genetic Network Programming (GNP) to be used for creating trading rules on stocks, where a new method named GNP with Subroutines has been proposed. Compared to the conversional GNP, a new kind of node named subroutines node is added, which can call subprograms (subroutines) from GNP main programs. This reusable subroutines, which has judgment...
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