Dr Neil Urquhart N.Urquhart@napier.ac.uk
Lecturer
An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems
Urquhart, Neil; Powers, Simon T.
Authors
Dr Simon Powers S.Powers@napier.ac.uk
Lecturer
Abstract
We present an agent based framework for improving multi-stakeholder optimisation problems, which we define as optimisation problems where the solution is utilised by a number of stakeholders who have their own local preferences. We explore our ideas within the domain of the University Timetabling Problem, demonstrating how a solution created by traditional timetabling methods may be further improved from the perspective of individual stakeholders (students) by agent based methods. We also note that this approach lends itself to increasing the level of trust in such systems by potentially allowing the stakeholders to view the actions taken by agents on their behalf.
Citation
Urquhart, N., & Powers, S. T. (2019). An Agent Based Technique for Improving Multi-Stakeholder Optimisation Problems. In PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection: vol 1 – Main track and Demos proceedings (285-289). https://doi.org/10.1007/978-3-030-24209-1_32
Conference Name | PAAMS 2019: International Conference on Practical Applications of Agents and Multi-Agent Systems |
---|---|
Conference Location | Avila, Spain |
Start Date | Jun 26, 2019 |
End Date | Jun 28, 2019 |
Acceptance Date | Mar 11, 2019 |
Online Publication Date | Jun 26, 2019 |
Publication Date | Jun 26, 2019 |
Deposit Date | Mar 12, 2019 |
Publicly Available Date | Jun 27, 2020 |
Publisher | Springer |
Pages | 285-289 |
Series Title | Lecture Notes in Computer Science |
Series Number | 11523 |
Book Title | PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection: vol 1 – Main track and Demos proceedings |
ISBN | 978-3-030-24208-4 |
DOI | https://doi.org/10.1007/978-3-030-24209-1_32 |
Keywords | Timetabling, optimisation, Real-World, explainability |
Public URL | http://researchrepository.napier.ac.uk/Output/1654812 |
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