An approach to creating a thinking process in systems empowered with intelligence using 3D environments

Author:

Skuliabina Olga,Petrova Kristina,Nass Oksana,Bapiyev Ideyat,Vakhitova Aizada,Baigubenova Saya

Abstract

The study is aimed at solving the problem of thinking and the sources of building thought processes in systems empowered with intelligence as one of the fundamental steps to the creation of artificial intelligence. Artificial intelligence performs creative functions traditionally considered human prerogative, using computer programs to understand human intelligence and not being limited to biologically plausible methods. In this regard the evolution of a traditional computer program into a system capable of self-creation is being implemented, depending on the conditions of the external and internal events and processes. The article authors present a number of intermediate results of the research in the field of advanced technologies and artificial intelligence achieved on the basis of experiments run on the study of the semantic structures construction – sources aimed at shaping a thinking process in systems empowered with intelligence. The research carried out by the authors of the article contributes to building of basic algorithms as a parametrically polymorphic system. Scheme of one of the main functions of the master algorithm is presented. An array of constructions, semantically related and called by a route determined by a vector, the direction of which is aimed at minimal costs winning, which together act as the fundamental method for creating a master algorithm.

Publisher

EDP Sciences

Subject

General Medicine

Reference12 articles.

1. Astakhov M.I., Kamnev Ye.O., Maksimov A.G., Molodezh'. Tekhnika. Kosmos: trudy trinadtsatoy obshcheros. molo dezhn. nauch.-tekhn. konf. 2.2 (2021)

2. Flach P.A., Machine Learning. The Art and Science of Algorithms that Make Sense of Data (United States of America by Cambridge University Press, New York, 2012) URL: www.cambridge.org/9781107096394

3. Helmuth T., Kelly P., Genet Program Evolvable, 375–404 (2022) https://doi.org/10.1007/s10710-022-09434-y

4. Le T.T., La Cava W., Romano J.D., Gregg J.T. et al, Pmlb v1.0: an open source dataset collection for benchmarking machine learning methods (2020) https://arxiv.org/abs/2012.00058

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3