人工智能:概念概述,方法方法和选择指标

M. Bogner, M. Steiger, F. Wiesinger
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引用次数: 0

摘要

在过去的几年里,人工智能领域出现了复兴,也被称为AI。这个主题的各种可能的概念导致了对各种方法的适当了解的冲动。本文着重于解释关于人工智能的主要和最相关的理论概念,并根据衍生的标准对它们进行评级。为此,我们分析了这些学习概念最显著的表现形式,以确定其核心特征。选择指标是基于这些知识得出的,并根据工业环境进行选择。此外,还开发了一种系统的方法,以便用户根据给定的标准选择适当的概念。本文的最终结果是一组图表,根据所发现的标准说明了不同的人工智能概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence: concept overview, methodological approaches and choice metrics
During the last couple of years there has been a renaissance in the field of artificial intelligence, also called AI. A wide diversity of possible concepts to this topic leads to the compulsion to be properly informed about a variety of approaches. This paper focuses on explaining the primary and most relevant theoretical concepts in regard to artificial intelligence and to rate them based on derived criteria. To achieve this, the most significant manifestations of these learning concepts are analyzed to identify their core characteristics. Choice metrics are derived based on this knowledge and selected with regard to an industrial environment. Additionally, a methodical approach is developed to ease the user’s choice of an appropriate concept according to the given criteria. The final result of this paper is a set of diagrams that illustrate the different artificial intelligence concepts based on the found criteria.
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