选择,生长和形成. 图灵的两条生物路径通向智能机械
Hajo Greif1, Adam P Kubiak1, Paweł Stacewicz1
1Philosophy of Computing Group, Faculty of Administration and Social Sciences, Warsaw University of Technology, Plac Politechniki 1, 00-661 Warsaw, Poland.
Studies in history and philosophy of science
|July 3, 2024
概括
艾伦·图灵 (Alan Turing) 是一个伟大的科学家.
科学领域:
- 人工智能的哲学 人工智能的哲学
- 计算机的历史 计算机的历史
- 发展生物学 发展生物学
背景情况:
- 艾伦·图灵关于"组织"机器 (1948) 和数学形态生成 (1952) 的工作是不同的,但相关的.
- 这些理论探讨了诸如达尔文学说在学习和模式形成中的选择等生物学概念.
- 图灵的计算建模 (1936) 为这两者提供了一个框架.
研究的目的:
- 调查图灵的生物学思想对他对智能机械概念的影响.
- 探索他关于机器学习和生物模式形成的理论之间的联系.
- 检查这些理论如何,尽管有局限性,建议认知作为一个生物,体现现象.
主要方法:
- 追踪图灵早期关于机器的研究与他后来关于形态发生的研究之间的概念联系.
- 分析图灵关于学习过程与大脑解剖学之间的关系的猜测.
- 使用·诺伊曼的细胞自动机和仿生方法作为比较框架.
主要成果:
- 图灵关于"组织"机器和形态发生的理论虽然不同,但共享一个计算基础.
- 这两种理论都部分表明认知是一种生物和体现过程.
- 图灵计算方法的局限性阻止了对认知的直接建模.
结论:
- "主动"的性质和物质实现对于实现智能机器至关重要.
- 更明确地连接图灵的生物学理论可以促进对体内认知的理解.
- 进一步的研究可以将图灵的基本思想与当代的仿生学和计算方法联系起来.
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