File(s) not publicly available

Self-explanatory capabilities in intelligent decision support systems in resource management

conference contribution
posted 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.

Funding

Other

History

Editor

Barolli L; Hussain FK; Ikeda M

Volume

AISC 993

Start Page

356

End Page

367

Number of Pages

12

Start Date

03/07/2019

Finish Date

05/07/2019

eISSN

2194-5365

ISSN

2194-5357

ISBN-13

9783030223533

Location

Sydney, NSW, Australia

Publisher

Springer

Place of Publication

Cham, Switzerland

Peer Reviewed

Yes

Open Access

No

Author Research Institute

Centre for Intelligent Systems

Era Eligible

Yes

Name of Conference

13th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS 2019)