Makoto Obayashi

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Although a large number of researches have been carried out into the analysis of nonlinear phenomena, little is reported about using reinforcement learning, which is widely used in artificial intelligent, intelligent control, and other fields. Here, we consider the problem of chaotic time series using a self-organized fuzzy neural network and reinforcement(More)
A new chaotic memory search model based on associative dynamics using features in stored patterns is proposed. In the present paper, two kinds of features are considered; external and internal ones. The former is assigned by a designer and the latter is automatically assigned by competitive learning. The control of chaotic and static states is realized(More)
This paper presents an effective TSP (Travel-ing Salesman Problem) solver for large-scale problems using neural networks. Firstly, in the proposed method, an intractable large-scale TSP is divided into some tractable small-scale problems (clusters) using a clustering technique. Secondly, a visiting order of clusters is determined using chaotic neural(More)
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