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在解释演绎推理时,是否有理由对符号计算主义方法提出质疑?

Are there reasons to challenge a symbolic computationalist approach in explaining deductive reasoning?

作者信息

Faiciuc Lucia E

机构信息

Department for Social and Human Sciences Research, Romanian Academy, Cluj-Napoca Branch, Cluj-Napoca, Romania.

出版信息

Integr Psychol Behav Sci. 2008 Jun;42(2):212-8. doi: 10.1007/s12124-007-9047-2. Epub 2008 Jan 15.

DOI:10.1007/s12124-007-9047-2
PMID:18196355
Abstract

The majority of the existing theories explaining deductive reasoning could be included in a classic computationalist approach of the cognitive processes. In fact, deductive reasoning could be seen to be the pinnacle of the symbolic computationalism, its last fortress to be defended in the face of new, dynamic, and ecological perspectives over cognition. But are there weak points in that position regarding deductive reasoning? What would be the reasons for which new perspectives could gain in credibility? What could be their most important tenets? The answers given to those questions in the paper include two main points. The first one is that the present empirical data could not sustain unambiguously one view over the other, that they are obtained in artificial experimental conditions, and that there are data that are not easily explainable using the traditional computationalist paradigm. The second one is that approaching the deductive reasoning from dynamic and ecological perspectives could have significant advantages. The most obvious one is the possibility to integrate more easily the research regarding the deductive reasoning with the results obtained in other domains of the psychology (especially in what respects the lower cognitive processes), in artificial intelligence or in neurophysiology. The reasons for that would be that such perspectives, as they are sketched in the paper, would imply, essentially, processes of second-order pattern formation and recognition (as it is the case for perception), embodied cognition, and dynamic processes as the brain ones are.

摘要

大多数现有的解释演绎推理的理论都可以纳入认知过程的经典计算主义方法之中。事实上,演绎推理可被视为符号计算主义的巅峰,是在面对关于认知的新的、动态的和生态的观点时需要捍卫的最后一座堡垒。但是,在演绎推理这一立场上是否存在弱点呢?新观点获得可信度的原因是什么?它们最重要的原则可能是什么?本文对这些问题的回答包括两个要点。第一个要点是,目前的实证数据无法明确支持一种观点优于另一种观点,这些数据是在人工实验条件下获得的,而且存在一些数据难以用传统的计算主义范式来解释。第二个要点是,从动态和生态的角度研究演绎推理可能具有显著优势。最明显的优势是能够更轻松地将演绎推理的研究与心理学其他领域(特别是在较低层次认知过程方面)、人工智能或神经生理学中获得的结果相结合。其原因在于,正如本文所概述的,这些观点本质上意味着二阶模式形成和识别过程(就像感知那样)、具身认知以及与大脑过程一样的动态过程。

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Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems.从混沌动力系统的角度对动态神经活动进行解释。
Behav Brain Sci. 2001 Oct;24(5):793-810; discussion 810-48. doi: 10.1017/s0140525x01000097.
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