Genetic Network Programming with Intron-Like Nodes

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  • Mabu Shingo
    Graduate School of Information, Production and Systems, Waseda University
  • Chen Yan
    Graduate School of Information, Production and Systems, Waseda University
  • Eto Shinji
    Information, Production and Systems Research Center, Waseda University
  • Shimada Kaoru
    Information, Production and Systems Research Center, Waseda University
  • Hirasawa Kotaro
    Graduate School of Information, Production and Systems, Waseda University

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  • 擬似イントロンノードを用いた遺伝的ネットワークプログラミング
  • ギジ イントロン ノード オ モチイタ イデンテキ ネットワーク プログラミング

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Abstract

Recently, Genetic Network Programming (GNP) has been proposed, which is an extension of Genetic Algorithm(GA) and Genetic Programming(GP). GNP can make compact programs and can memorize the past history in it implicitly, because it expresses the solution by directed graphs and therefore, it can reuse the nodes. In this research, intron-like nodes are introduced for improving the performance of GNP. The aim of introducing intron-like nodes is to use every node as much as possible. It is found from simulations that the intron-like nodes are useful for improving the training speed and generalization ability.

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