進化計算学会論文誌
Online ISSN : 2185-7385
ISSN-L : 2185-7385
論文
ノードの種類・内容も探索対象とする確率モデル構築型遺伝的ネットワークプログラミング
元木 達也小林 涼
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2015 年 6 巻 1 号 p. 13-30

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In this paper, we propose an estimation of distribution algorithm (EDA) for finding a good individual in getetic network programming (GNP). Our EDA is an extension of Li et al.(2009)'s probabilistic model building genetic network programming (PMBGNP). Each individual in GNP has a directed graph structure composed of a start node, judgment nodes, processing nodes and arcs between nodes. While Li et al.'s PMBGNP builds probabilistic distributions of terminal points of arcs, our PMBGNP also builds probabilistic distributions of function assignments to nodes as well as distributions of terminal points of arcs. Our PMBGNP searchs over the space of possible combinations of function assignments to nodes and terminal points of arcs, and so dispenses with any breakdown of the number of nodes. Two maze problems and the 11-multiplexer problem are used to evaluate the performance of the proposed search method. The experimental results show that our PMBGNP finds the optimum solutions of the tested problems in some moderate probability.

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