{"title":"Cognitive Tools for Abstract Thinking Autonomous Intelligent Mobile Systems","authors":"V. Melekhin, M. Khachumov","doi":"10.17587/mau.24.317-326","DOIUrl":null,"url":null,"abstract":"The actual problems of artificial intelligence related to the development of tools for abstract thinking of autonomous intelligent mobile systems are being solved, which allow planning purposeful behavior in hard-to-reach and aggressive environments for humans. Cognitive tools are proposed that provide intelligent systems with the ability to organize purposeful multi-stage activities related to solving complex problems, when a behavior plan is automatically built in some conditions of a problematic environment, and a given behavior goal is achieved in other operating conditions that are beyond the resolution of technical vision. An important feature of the proposed typical elements of knowledge representation and processing is that they allow intelligent systems to organize the output of solving complex problems, relying only on the data stored in the knowledge representation model and coming from the current operating conditions. In the general case, the developed knowledge model of intelligent systems for various purposes consists of declarative and procedural typical elements of their representation. For a formal description of typical elements of declarative knowledge representation, traditional semantic networks and various sets of restrictions are used, reflecting additional conditions for the future functioning of autonomous mobile intelligent systems. As for the formal description of the typical elements of the representation of procedural knowledge, regardless of a specific subject area, fuzzy semantic networks are used for this. This allows autonomous intelligent mobile systems to adapt to specific operating conditions in underdetermined problematic environments and perform complex tasks formulated by them on this basis. The practical significance of the results obtained lies in the effectiveness of their use for the development of intelligent problem solvers that provide autonomous intelligent mobile systems for various purposes with the ability to perform complex tasks in a priori underdetermined problematic environments by adapting the purposeful activity plan formed in general form to specific current operating conditions.","PeriodicalId":36477,"journal":{"name":"Mekhatronika, Avtomatizatsiya, Upravlenie","volume":"129 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mekhatronika, Avtomatizatsiya, Upravlenie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17587/mau.24.317-326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The actual problems of artificial intelligence related to the development of tools for abstract thinking of autonomous intelligent mobile systems are being solved, which allow planning purposeful behavior in hard-to-reach and aggressive environments for humans. Cognitive tools are proposed that provide intelligent systems with the ability to organize purposeful multi-stage activities related to solving complex problems, when a behavior plan is automatically built in some conditions of a problematic environment, and a given behavior goal is achieved in other operating conditions that are beyond the resolution of technical vision. An important feature of the proposed typical elements of knowledge representation and processing is that they allow intelligent systems to organize the output of solving complex problems, relying only on the data stored in the knowledge representation model and coming from the current operating conditions. In the general case, the developed knowledge model of intelligent systems for various purposes consists of declarative and procedural typical elements of their representation. For a formal description of typical elements of declarative knowledge representation, traditional semantic networks and various sets of restrictions are used, reflecting additional conditions for the future functioning of autonomous mobile intelligent systems. As for the formal description of the typical elements of the representation of procedural knowledge, regardless of a specific subject area, fuzzy semantic networks are used for this. This allows autonomous intelligent mobile systems to adapt to specific operating conditions in underdetermined problematic environments and perform complex tasks formulated by them on this basis. The practical significance of the results obtained lies in the effectiveness of their use for the development of intelligent problem solvers that provide autonomous intelligent mobile systems for various purposes with the ability to perform complex tasks in a priori underdetermined problematic environments by adapting the purposeful activity plan formed in general form to specific current operating conditions.