D. Mutin, Alexey Kaperko, Sergey Sorokin, Dmitriy Sotnikov, I. Atlasov, Nikita Ryndin
{"title":"Automation of adaptive control of complex objects states trajectories in artificial\n intelligence systems","authors":"D. Mutin, Alexey Kaperko, Sergey Sorokin, Dmitriy Sotnikov, I. Atlasov, Nikita Ryndin","doi":"10.59035/zdgm9286","DOIUrl":null,"url":null,"abstract":"Today, the problem of automating the control of the individual trajectory of the\n states of complex objects is relevant. It is necessary to influence the individual\n trajectory of the object's states, guided by certain parameters. The reaction should be\n adequate to change these parameters. The aim of the work is reasonable automation of\n adaptive control of complex objects and trajectories in artificial intelligence systems.\n Tasks to be solved: (1) Identification and evaluation of criteria by which it is\n possible to determine the level of the object's condition with a high degree of\n probability. (2) Creation of such a mechanism for issuing control actions to an object,\n on the basis of which it will be possible to create fully automated control trajectories\n that require a minimum of operator participation in the operation of the finished\n system","PeriodicalId":42317,"journal":{"name":"International Journal on Information Technologies and Security","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal on Information Technologies and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59035/zdgm9286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Today, the problem of automating the control of the individual trajectory of the
states of complex objects is relevant. It is necessary to influence the individual
trajectory of the object's states, guided by certain parameters. The reaction should be
adequate to change these parameters. The aim of the work is reasonable automation of
adaptive control of complex objects and trajectories in artificial intelligence systems.
Tasks to be solved: (1) Identification and evaluation of criteria by which it is
possible to determine the level of the object's condition with a high degree of
probability. (2) Creation of such a mechanism for issuing control actions to an object,
on the basis of which it will be possible to create fully automated control trajectories
that require a minimum of operator participation in the operation of the finished
system