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Недедуктивная логика и проблема компьютерной репрезентации знания

Недедуктивная логика и проблема компьютерной репрезентации знания

Abstract

В статье продолжается дальнейшая разработка концепции компьютерной репрезентологии, в рамках которой проводится философско-методологический анализ недедуктивных моделей компьютерной репрезентации знания, которые представляют собой особый класс логических моделей компьютерной репрезентации знания. В работе исследуются такие виды недедуктивных моделей компьютерной репрезентации знания как индуктивные модели, псевдофизические логики, продукционные модели и модели, формализующие модифицируемые рассуждения. Отмечаются достоинства и недостатки логических моделей.

The article considers further development of the concept of computer representology for held philosophical and methodological analysis of nondeductive models of computer representations of knowledge, which are a special class of logical models of computer representations of knowledge. This paper investigates these types of nondeductive models of computer representations of knowledge as inductive models, pseudo-physical logics, production models and models formalizing modifiable reasoning. The authors marked advantages and disadvantages of logical models.

Keywords

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ (ИИ), КОМПЬЮТЕРНАЯ РЕПРЕЗЕНТОЛОГИЯ, КОНЦЕПЦИИ КОМПЬЮТЕРНОЙ РЕПРЕЗЕНТАЦИИ ЗНАНИЯ, ЛОГИЧЕСКАЯ КОНЦЕПЦИЯ КОМПЬЮТЕРНОЙ РЕПРЕЗЕНТАЦИИ ЗНАНИЯ, НЕДЕДУКТИВНЫЕ МОДЕЛИ КОМПЬЮТЕРНОЙ РЕПРЕЗЕНТАЦИИ ЗНАНИЯ, ИНДУКТИВНЫЕ МОДЕЛИ, ПСЕВДОФИЗИЧЕСКИЕ ЛОГИКИ, МОДЕЛИ, ФОРМАЛИЗУЮЩИЕ МОДИФИЦИРУЕМЫЕ РАССУЖДЕНИЯ, ПРОДУКЦИОННЫЕ МОДЕЛИ, ARTIFICIAL INTELLIGENCE (AI)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold