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Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach

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Open access
Authors
Tan, Terence
Tan, Tele
West, Geoff
Low, S.
Date
2012
Type
Conference Paper

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Tan, Terence and Tan, Tele and West, Geoff and Low, Siow Yong. 2012. Learning and Cooperating Multi-Agent Scheduling Repair Using a Provenance-Centred Approach, in 5th International Conference on Human System Interaction (HSI), Jun 6-8 2012. Perth, WA: IEEE.
Source Title
5th Int. Conf. on Human System Interaction
Source Conference
HSI2012
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Abstract

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.