A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results

O. Kazík, K. Pesková, M. Pilát, Roman Neruda
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引用次数: 3

Abstract

We present a description of our multi-agent system where computational intelligence methods are embodied as software agents. This system is designed in order to allow easy experiments with learning, meta learning, gathering experience based on previous computations, and recommending suitable methods for particular data. The architecture of the system is presented and its meta learning abilities are demonstrated on a set of experiments with neural network models and both evolutionary and local search heuristics.
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一种新的元学习系统及其在计算代理结果优化中的应用
我们描述了我们的多智能体系统,其中计算智能方法体现为软件代理。该系统的设计是为了允许简单的学习实验,元学习,根据以前的计算收集经验,并为特定数据推荐合适的方法。介绍了该系统的体系结构,并通过神经网络模型以及进化和局部搜索启发式的一系列实验证明了其元学习能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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