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Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism

机译:信任的基础:基本的认知不透明度和计算可靠性

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Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations (Parker in Synthese 169(3):483-496, 2009; Morrison in Philos Stud 143(1):33-57, 2009), the nature of computer data (Barberousse and Vorms, in: Duran, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Duran, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of computer simulations (Krohs in Int Stud Philos Sci 22(3):277-292, 2008; Duran in Int Stud Philos Sci 31(1):27-45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of (un)successful implementations, and the role of expert knowledge in simulations.
机译:与计算机模拟有关的几个哲学问题都依赖于模拟结果值得信赖的假设。这些例子包括关于计算机模拟的实验作用的辩论(Parker in Synthese 169(3):483-496,2009; Morrison in Philos Stud 143(1):33-57,2009),计算机数据的性质( Barberousse and Vorms,在:杜兰,阿诺德(eds)计算机模拟和科学实验的变化面孔,剑桥学者出版社,巴塞罗那,2013; Humphreys,在:杜兰,阿诺德(eds)计算机模拟和科学实验的变化面孔,剑桥学者出版社,巴塞罗那,2013年)以及计算机模拟的解释能力(Krohs in Int Stud Philos Sci 22(3):277-292,2008; Duran in Int Stud Philos Sci 31(1):27-45,2017) )。本文的目的是证明这些作者的正确假设是,当计算机仿真是可靠的过程时,计算机仿真的结果将受到信任。在简短地重构了认识论上的不透明性问题之后,本文广泛地阐述了计算可靠性,这是一种指定形式的过程可靠性,其中心是计算机模拟。本文最后讨论了计算可靠性的四个来源,即验证和确认,用于计算机仿真的鲁棒性分析,(失败的)实现历史以及专家知识在仿真中的作用。

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