Physical benchmarks for testing algorithms

IF 18.8 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Nature Machine Intelligence Pub Date : 2025-02-20 DOI:10.1038/s42256-025-00999-8

Jakob Zeitler

引用次数: 0

Abstract

The development of comprehensive benchmarks to assess the performance of algorithms on causal tasks is an important, emerging area. The introduction of two physical ‘causal chamber’ systems serves as a firm step towards future, more reliable benchmarks in the field.

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开发综合基准来评估算法在因果任务上的性能是一个重要的新兴领域。两个物理 "因果室 "系统的引入，为该领域未来更可靠的基准迈出了坚实的一步。

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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来源期刊

Nature Machine Intelligence Multiple-

CiteScore

36.90

自引率

2.10%

发文量

127

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