{"title":"TEMPORAL-ORIENTED MODEL OF CAUSAL RELATIONSHIP FOR CONSTRUCTING EXPLANATIONS FOR DECISION-MAKING PROCESS","authors":"S. Chalyi, V. Leshchynskyi","doi":"10.20998/2522-9052.2022.3.09","DOIUrl":null,"url":null,"abstract":"The subject of research in the article is the decision-making process in intelligent systems. The goal is to develop a model of the causal relationship between the states of the decision-making process in an intelligent information system, taking into account the temporal aspect of this process, in order to build cause-and-effect relationships between the actions of the process and further use these dependencies to form explanations for the sequence of actions to obtain a decision. The formation of causal relations between the states of the decision-making process makes it possible to substantiate the sequence of actions of this process, considering incomplete information regarding external influences on this process. Tasks: structuring the decision-making process in an intelligent information system as a specialized business process; development of a three-element model of the causal relationship between the states of the decision-making process, considering the temporal aspect of this process; substantiation of the possibility of using three-element relationships to build causal dependencies for decision making in intelligent systems. The approaches used are: the set-theoretical approach used to describe the elements of the decision-making process in intelligent systems; a logical approach that provides a representation of the relationship between the states of the decision-making process; probabilistic approach to describe the probabilistic component of the decision-making process. The following results are obtained. The decision-making process in an intelligent information system was structured as a specialized business process that, using additional information from the user, turns the input data into a result that is valuable for this user; a three-element model of the causal relationship between the states of the decision-making process is proposed, which makes it possible to take into account external influences on the process; using a probabilistic approach, the possibility of using three-element causal relations to describe the decision-making process in intelligent systems is substantiated, taking into account uncontrolled external influences. Conclusions. The scientific novelty of the obtained results is as follows. A three-element model of the causal relationship between the states of the decision-making process is proposed, based on a model of a temporal rule of the \"future\" type, containing a state-cause, a state-effect and an intermediate state that reflects external influences. The model makes it possible to build a base of cause-and-effect dependencies for the decision-making process in an intelligent information system, considering external influences and use these dependencies to build explanations for this process.","PeriodicalId":34701,"journal":{"name":"Suchasni informatsiini sistemi","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Suchasni informatsiini sistemi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20998/2522-9052.2022.3.09","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The subject of research in the article is the decision-making process in intelligent systems. The goal is to develop a model of the causal relationship between the states of the decision-making process in an intelligent information system, taking into account the temporal aspect of this process, in order to build cause-and-effect relationships between the actions of the process and further use these dependencies to form explanations for the sequence of actions to obtain a decision. The formation of causal relations between the states of the decision-making process makes it possible to substantiate the sequence of actions of this process, considering incomplete information regarding external influences on this process. Tasks: structuring the decision-making process in an intelligent information system as a specialized business process; development of a three-element model of the causal relationship between the states of the decision-making process, considering the temporal aspect of this process; substantiation of the possibility of using three-element relationships to build causal dependencies for decision making in intelligent systems. The approaches used are: the set-theoretical approach used to describe the elements of the decision-making process in intelligent systems; a logical approach that provides a representation of the relationship between the states of the decision-making process; probabilistic approach to describe the probabilistic component of the decision-making process. The following results are obtained. The decision-making process in an intelligent information system was structured as a specialized business process that, using additional information from the user, turns the input data into a result that is valuable for this user; a three-element model of the causal relationship between the states of the decision-making process is proposed, which makes it possible to take into account external influences on the process; using a probabilistic approach, the possibility of using three-element causal relations to describe the decision-making process in intelligent systems is substantiated, taking into account uncontrolled external influences. Conclusions. The scientific novelty of the obtained results is as follows. A three-element model of the causal relationship between the states of the decision-making process is proposed, based on a model of a temporal rule of the "future" type, containing a state-cause, a state-effect and an intermediate state that reflects external influences. The model makes it possible to build a base of cause-and-effect dependencies for the decision-making process in an intelligent information system, considering external influences and use these dependencies to build explanations for this process.