Open AccessFormalization of the meaning. Part 3. Formation of contexts
Author(s) -
Alexey Redozubov,
AUTHOR_ID
Publication year - 2021
Publication title -
ontologiâ proektirovaniâ
Language(s) - English
Resource type - Journals
eISSN - 2313-1039
pISSN - 2223-9537
DOI - 10.18287/2223-9537-2021-11-4-437-449
Subject(s) - interpretation (philosophy) , computer science , meaning (existential) , space (punctuation) , point (geometry) , set (abstract data type) , cover (algebra) , context (archaeology) , observable , artificial intelligence , epistemology , theoretical computer science , cognitive science , mathematics , psychology , engineering , programming language , mechanical engineering , paleontology , philosophy , physics , geometry , quantum mechanics , biology , operating system
The previous parts of this article have attempted to begin describing an approach to building strong artificial intelli-gence based on sense of information. A model was proposed in which concepts were described through related points of view. The point of view was set as a context that changes the original description to its interpretation. It was shown that the meaningfulness of the interpretation can be judged by its adequacy to the memory of previous experience. The space of contexts is described, which defines a system of concepts that cover a certain subject area. In this part of the article, an algorithm is described that allows you to create an initial system of concepts based on the observable signs of phe-nomena, and move from it to the contexts corresponding to these concepts. For the space of contexts, a method for cre-ating concept codes is proposed, which allows concept codes to convey the system of their internal proximity, a com-parison with convolutional networks is made. Explanations of the proposed approach are considered on the example of training the visual cortex.