Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach
The timetabling problem is to find a timetable solution by assigning time and resources to sessions that satisfy a set of constraints. Traditionally, research has focused on optimization towards a final solution but this paper focuses on minimizing disturbance impact due to changing conditions. A Mu...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/26518 |
| _version_ | 1848752009468968960 |
|---|---|
| author | Tan, Terence Tan, Tele West, Geoff Low, S. |
| author2 | Not known |
| author_facet | Not known Tan, Terence Tan, Tele West, Geoff Low, S. |
| author_sort | Tan, Terence |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The timetabling problem is to find a timetable solution by assigning time and resources to sessions that satisfy a set of constraints. Traditionally, research has focused on optimization towards a final solution but this paper focuses on minimizing disturbance impact due to changing conditions. A Multi-Agent System (MAS) is proposed in which users are represented as autonomous agents negotiating with one another to repair a timetable. From repeated negotiations, agents learn to develop a model of other agent's preferences. The MAS is simulated on a factorial experiment set up and varying the cooperation level, learning model and selection strategy. A provenance-centred approach is adopted to improve the human aspect of timetabling to allow users to derive the steps towards a solution and make changes to influence the solution. |
| first_indexed | 2025-11-14T08:01:48Z |
| format | Conference Paper |
| id | curtin-20.500.11937-26518 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:01:48Z |
| publishDate | 2012 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-265182017-09-13T15:26:49Z Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach Tan, Terence Tan, Tele West, Geoff Low, S. Not known The timetabling problem is to find a timetable solution by assigning time and resources to sessions that satisfy a set of constraints. Traditionally, research has focused on optimization towards a final solution but this paper focuses on minimizing disturbance impact due to changing conditions. A Multi-Agent System (MAS) is proposed in which users are represented as autonomous agents negotiating with one another to repair a timetable. From repeated negotiations, agents learn to develop a model of other agent's preferences. The MAS is simulated on a factorial experiment set up and varying the cooperation level, learning model and selection strategy. A provenance-centred approach is adopted to improve the human aspect of timetabling to allow users to derive the steps towards a solution and make changes to influence the solution. 2012 Conference Paper http://hdl.handle.net/20.500.11937/26518 10.1109/HSI.2012.30 IEEE fulltext |
| spellingShingle | Tan, Terence Tan, Tele West, Geoff Low, S. Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title | Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title_full | Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title_fullStr | Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title_full_unstemmed | Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title_short | Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach |
| title_sort | learning and cooperating multi-agent scheduling repair using a provenance-centred approach |
| url | http://hdl.handle.net/20.500.11937/26518 |