Efficient Organization of Network Topology based on Reinforcement Signals

Chyon Hae Kim, S. Sugano, T. Ogata
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引用次数: 1

Abstract

We developed a learning system for autonomous robots that allows for autonomous exploration of the effective output, and has simple external parameters and a low calculation cost. We propose the concept of self-organizing network elements (SONE) for creating learning systems with these characteristics. We created and evaluated a self-organizing logic circuit by using this concept. Our results indicated this learning system had the characteristics
基于强化信号的网络拓扑高效组织
我们为自主机器人开发了一个学习系统,允许自主探索有效输出,并且具有简单的外部参数和低计算成本。我们提出了自组织网络元素(SONE)的概念来创建具有这些特征的学习系统。我们利用这个概念创建并评估了一个自组织逻辑电路。结果表明,该学习系统具有以下特点
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