诱拐的生态认知模型2

Q1 Mathematics Journal of Applied Logic Pub Date : 2016-05-01 DOI:10.1016/j.jal.2016.02.001
Lorenzo Magnani
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引用次数: 24

摘要

在《诱拐的生态认知模型》一文中[66],我阐述了诱拐生态认知模型(EC-Model)的主要特征。为了进一步描述John Woods[94]最近提出的“逻辑的自然化”,我现在将进一步分析溯因论的一些性质,这些性质从逻辑的角度来看是必不可少的。在处理所谓的“推理问题”时,我将选择更一般的输入和输出概念,而不是前提和结论的概念,并表明在这个框架中可以推导出两个结果,有助于澄清溯因推理的基本逻辑方面:1)它是更自然的接受“多通道”和“上下文相关的”字符的推论,2)推断不仅仅是构思的过程中导致的“代输出”或证明,在传统的演绎证明和标准视图,而是从这个角度看诱导的推论可以被视为相关逻辑流程的输入和输出失败持有对方预期的关系,解决方案涉及到输入的修改,而不是输出的修改。找到溯因解的机会似乎仍然取决于亚里士多德的“引开”(παγωγή)概念,也就是说,取决于开始应用实现适当形式推理引擎的补充逻辑。我要强调的一个重要结果是,不相关和不可信并不总是冒犯理性。此外,我们不能确定,更广泛地说,我们猜测的假设是合理的(即使我们知道,提前寻找合理性是一种人类有益而明智的启发式),事实上,一个不合理的假设后来可能会变得合理。在文章的最后一部分,我将描述,如果我们希望自然化溯因过程的逻辑及其特殊的结果关系,我们应该参考以下几个主要方面:“情境性优化”,“可变性最大化”的输入和输出,以及高“信息敏感性”。此外,我将指出溯因的逻辑必须承认记录溯因推理实践的“前世”的重要性,这与传统的论证性理想系统以我所谓的“无记忆最大化”为原型的事实相反。
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The eco-cognitive model of abduction II

In the companion article “The eco-cognitive model of abduction” [66] I illustrated the main features of my eco-cognitive model of abduction (EC-Model). With the aim of delineating further aspects of that “naturalization of logic” recently urged by John Woods [94] I will now set out to further analyze some properties of abduction that are essential from a logical standpoint. When dealing with the so-called “inferential problem”, I will opt for the more general concepts of input and output instead of those of premisses and conclusions, and show that in this framework two consequences can be derived that help clarify basic logical aspects of abductive reasoning: 1) it is more natural to accept the “multimodal” and “context-dependent” character of the inferences involved, 2) inferences are not merely conceived of in the terms of the process leading to the “generation of an output” or to the proof of it, as in the traditional and standard view of deductive proofs, but rather, from this perspective abductive inferences can be seen as related to logical processes in which input and output fail to hold each other in an expected relation, with the solution involving the modification of inputs, not that of outputs. The chance of finding an abductive solution still appears to depend on the Aristotelian concept of “leading away” (ἀπαγωγή) I dealt with in the companion article, that is, on the starting of the application of a supplementary logic implementing an appropriate formal inference engine. An important result I will emphasize is that irrelevance and implausibility are not always offensive to reason. In addition, we cannot be sure, more broadly, that our guessed hypotheses are plausible (even if we know that looking – in advance – for plausibility is a human good and wise heuristic), indeed an implausible hypothesis can later on result plausible. In the last part of the article I will describe that if we wish to naturalize the logic of the abductive processes and its special consequence relation, we should refer to the following main aspects: “optimization of situatedness”, “maximization of changeability” of both input and output, and high “information-sensitiveness”. Furthermore, I will point out that a logic of abduction must acknowledge the importance of keeping record of the “past life” of abductive inferential praxes, contrarily to the fact that traditional demonstrative ideal systems are prototypically characterized by what I call “maximization of memorylessness”.

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来源期刊
Journal of Applied Logic
Journal of Applied Logic COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
1.13
自引率
0.00%
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0
审稿时长
>12 weeks
期刊介绍: Cessation.
期刊最新文献
Editorial Board Editorial Board Formal analysis of SEU mitigation for early dependability and performability analysis of FPGA-based space applications Logical Investigations on Assertion and Denial Natural deduction for bi-intuitionistic logic
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