Towards Unifying Perceptual Reasoning and Logical Reasoning

Fuente: arXiv
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Main Author: Kido, Hiroyuki
Format: Preprint
Published: 2022
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author Kido, Hiroyuki
author_facet Kido, Hiroyuki
contents An increasing number of scientific experiments support the view of perception as Bayesian inference, which is rooted in Helmholtz's view of perception as unconscious inference. Recent study of logic presents a view of logical reasoning as Bayesian inference. In this paper, we give a simple probabilistic model that is applicable to both perceptual reasoning and logical reasoning. We show that the model unifies the two essential processes common in perceptual and logical systems: on the one hand, the process by which perceptual and logical knowledge is derived from another knowledge, and on the other hand, the process by which such knowledge is derived from data. We fully characterise the model in terms of logical consequence relations.
format Preprint
id arxiv_https___arxiv_org_abs_2206_13174
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Towards Unifying Perceptual Reasoning and Logical Reasoning
Kido, Hiroyuki
Artificial Intelligence
An increasing number of scientific experiments support the view of perception as Bayesian inference, which is rooted in Helmholtz's view of perception as unconscious inference. Recent study of logic presents a view of logical reasoning as Bayesian inference. In this paper, we give a simple probabilistic model that is applicable to both perceptual reasoning and logical reasoning. We show that the model unifies the two essential processes common in perceptual and logical systems: on the one hand, the process by which perceptual and logical knowledge is derived from another knowledge, and on the other hand, the process by which such knowledge is derived from data. We fully characterise the model in terms of logical consequence relations.
title Towards Unifying Perceptual Reasoning and Logical Reasoning
topic Artificial Intelligence
url https://arxiv.org/abs/2206.13174