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Modeling Causal-Effect Relationships for Artificial Intelligence Applications
| Content Provider | Scilit |
|---|---|
| Author | Sandrasegaran, Kumbesan |
| Copyright Year | 2020 |
| Description | Cause-effect representations form the foundations for representing systems causality in a number of AI systems. Such a representation can be used for a number of different tasks. It can be used for simulating the behavior of a device, providing explanations about the operation of a device, generating diagnostic knowledge, etc. In this paper, a taxonomy of models of cause-effect relationships of device operation and how these models were used to generate diagnostic knowledge are presented. Book Name: Industrial and Engineering Applications of Artificial Intelligence and Expert Systems |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9780429332197-11&type=chapterpdf |
| Ending Page | 78 |
| Page Count | 6 |
| Starting Page | 73 |
| DOI | 10.1201/9780429332197-11 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-01-08 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Industrial and Engineering Applications of Artificial Intelligence and Expert Systems Hardware and Architecturee Models Behavior Causal Cause Effect Representations Effect Relationships Intelligence Explanations Artificial |
| Content Type | Text |
| Resource Type | Chapter |
