优化的极限

IF 4.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Minds and Machines Pub Date : 2024-01-01 Epub Date: 2023-04-06 DOI:10.1007/s11023-023-09633-1
Cesare Carissimo, Marcin Korecki
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引用次数: 0

摘要

优化是指根据目标函数找到最佳的可用对象。数学和定量科学在将问题表述为优化问题,以及构建从对象集合中找到最优对象的巧妙过程方面取得了巨大成功。随着大多数人都能轻松使用计算机,优化和优化过程在社会中发挥着非常广泛的作用。然而,适用于数学和抽象对象的优化过程是否能轻易应用于复杂而开放的社会系统,这一点并不明显。在本文中,我们提出了一个框架,以了解优化何时会受到限制,尤其是对复杂和开放的社会系统而言。
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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Limits of Optimization.

Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should be readily applied to complex and open social systems. In this paper we set forth a framework to understand when optimization is limited, particularly for complex and open social systems.

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来源期刊
Minds and Machines
Minds and Machines 工程技术-计算机:人工智能
CiteScore
12.60
自引率
2.70%
发文量
30
审稿时长
>12 weeks
期刊介绍: Minds and Machines, affiliated with the Society for Machines and Mentality, serves as a platform for fostering critical dialogue between the AI and philosophical communities. With a focus on problems of shared interest, the journal actively encourages discussions on the philosophical aspects of computer science. Offering a global forum, Minds and Machines provides a space to debate and explore important and contentious issues within its editorial focus. The journal presents special editions dedicated to specific topics, invites critical responses to previously published works, and features review essays addressing current problem scenarios. By facilitating a diverse range of perspectives, Minds and Machines encourages a reevaluation of the status quo and the development of new insights. Through this collaborative approach, the journal aims to bridge the gap between AI and philosophy, fostering a tradition of critique and ensuring these fields remain connected and relevant.
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