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生物学中的计算立场。

The computational stance in biology.

机构信息

Santa Fe Institute , 1399 Hyde Park Road, Santa Fe, NM 87501 , USA.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2019 Jun 10;374(1774):20180380. doi: 10.1098/rstb.2018.0380.

Abstract

The goal of this article is to call attention to, and to express caution about, the extensive use of computation as an explanatory concept in contemporary biology. Inspired by Dennett's 'intentional stance' in the philosophy of mind, I suggest that a 'computational stance' can be a productive approach to evaluating the value of computational concepts in biology. Such an approach allows the value of computational ideas to be assessed without being diverted by arguments about whether a particular biological system is 'actually computing' or not. Because there is sufficient difference of agreement among computer scientists about the essential elements that constitute computation, any doctrinaire position about the application of computational ideas seems misguided. Closely related to the concept of computation is the concept of information processing. Indeed, some influential computer scientists contend that there is no fundamental difference between the two concepts. I will argue that despite the lack of widely accepted, general definitions of information processing and computation: (1) information processing and computation are not fully equivalent and there is value in maintaining a distinction between them and (2) that such value is particularly evident in applications of information processing and computation to biology. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

摘要

本文旨在关注并谨慎对待计算在当代生物学中被广泛用作解释概念的现象。受丹尼特在心灵哲学中“意向立场”的启发,我认为“计算立场”可以成为评估生物学中计算概念价值的一种富有成效的方法。这种方法可以在不被关于特定生物系统是否“实际计算”的争论所转移的情况下,评估计算思想的价值。由于计算机科学家对构成计算的基本要素有足够的共识,因此任何关于计算思想应用的教条主义立场似乎都是有误导性的。与计算概念密切相关的是信息处理概念。事实上,一些有影响力的计算机科学家认为这两个概念没有根本区别。我将论证,尽管信息处理和计算没有被广泛接受的、通用的定义:(1) 信息处理和计算并不完全等同,在它们之间保持区分是有价值的;(2) 这种价值在将信息处理和计算应用于生物学时尤为明显。本文是“流动的大脑,坚实的大脑:分布式认知架构如何处理信息”这一主题特刊的一部分。

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