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Self-explanatory capabilities in intelligent decision support systems in resource management
conference contributionposted on 27.03.2020, 00:00 by Maneerat RumsamrongManeerat Rumsamrong, Andrew ChiouAndrew Chiou, Dujuan LiDujuan Li
Self-explanations in decision support systems need to be presented in parallel with considering and understanding the outcomes of advice from the expert system. This advice can realise benefits such as increased user acceptance and confidence in the adoption of the improved system. There are numerous categories of explanation, including the following. In order for an expert system to reach a conclusion, there needs to be: (1) justification and a record of the inferential steps; (2) an explicit knowledge of the underlying argument, or (3) explanation of the rationale behind each inferential measure taken by the expert system. This recommendation will result in more persuasive justification and lead to satisfaction, and acceptance of advice. For this reason, it is proposed to announce a discourse semantics approach to an Intelligent Decision Support System framework by the inclusion of a discourse layer. In this paper, the discourse semantics layer approach will be demonstrated to show the mechanism of how a fuzzy logic based expert system utilises justification techniques for advice offered in the problem of control and resource management. © 2020, Springer Nature Switzerland AG.