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COUNTERFACTUAL TEMPORAL MODEL OF CAUSAL RELATIONSHIPS FOR CONSTRUCTING EXPLANATIONS IN INTELLIGENT SYSTEMS
Author(s) -
Serhii Chalyi,
Volodymyr Leshchynskyi,
Irina Leshchynska
Publication year - 2021
Publication title -
vestnik nacionalʹnogo tehničeskogo universiteta "hpi". sistemnyj analiz, upravlenie i informacionnye tehnologii/vestnik nacionalʹnogo tehničeskogo universiteta "hpi". seriâ sistemnyj analiz, upravlenie i informacionnye tehnologii
Language(s) - English
Resource type - Journals
eISSN - 2410-2857
pISSN - 2079-0023
DOI - 10.20998/2079-0023.2021.02.07
Subject(s) - counterfactual thinking , causality (physics) , transitive relation , computer science , property (philosophy) , causal model , representation (politics) , causal chain , event (particle physics) , process (computing) , counterfactual conditional , causal structure , artificial intelligence , theoretical computer science , psychology , mathematics , social psychology , epistemology , philosophy , statistics , physics , combinatorics , quantum mechanics , politics , political science , law , operating system
The subject of the research is the processes of constructing explanations based on causal relationships between states or actions of an intellectualsystem. An explanation is knowledge about the sequence of causes and effects that determine the process and result of an intelligent informationsystem. The aim of the work is to develop a counterfactual temporal model of cause-and-effect relationships as part of an explanation of the process offunctioning of an intelligent system in order to ensure the identification of causal dependencies based on the analysis of the logs of the behavior ofsuch a system. To achieve the stated goals, the following tasks are solved: determination of the temporal properties of the counterfactual description ofcause-and-effect relationships between actions or states of an intelligent information system; development of a temporal model of causal connections,taking into account both the facts of occurrence of events in the intellectual system, and the possibility of occurrence of events that do not affect theformation of the current decision. Conclusions. The structuring of the temporal properties of causal links for pairs of events that occur sequentially intime or have intermediate events is performed. Such relationships are represented by alternative causal relationships using the temporal operators"Next" and "Future", which allows realizing a counterfactual approach to the representation of causality. A counterfactual temporal model of causalrelationships is proposed, which determines deterministic causal relationships for pairs of consecutive events and pairs of events between which thereare other events, which determines the transitivity property of such dependencies and, accordingly, creates conditions for describing the sequence ofcauses and effects as part of the explanation in intelligent system with a given degree of detail The model provides the ability to determine cause-andeffect relationships, between which there are intermediate events that do not affect the final result of the intelligent information system.

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