Using Graph Properties and Clustering Techniques to Select Division Mechanisms for Scalable Negotiations

Book Chapter (2017)
Author(s)

I. Marsa Maestre (University of Alcala)

Catholijn Jonker (TU Delft - Interactive Intelligence)

Mark Klein (Massachusetts Institute of Technology)

Enrique de la Hoz (University of Alcala)

Research Group
Interactive Intelligence
DOI related publication
https://doi.org/10.1007/978-3-319-51563-2_5
More Info
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Publication Year
2017
Language
English
Research Group
Interactive Intelligence
Volume number
674
Pages (from-to)
67-84
ISBN (print)
978-3-319-51561-8
ISBN (electronic)
978-3-319-51563-2

Abstract

This paper focuses on enabling the use of negotiation for complex system optimisation, which main challenge nowadays is scalability. Our hypothesis is that analysing the underlying network structure of these systems can help divide the problems in subproblems which facilitate distributed decision making through negotiation in these domains. In this paper, we verify this hypothesis with an extensive set of scenarios for a proof-of-concept problem. After selecting a set of network metrics for analysis, we cluster the scenarios according to these metrics and evaluate a set of mediation mechanisms in each cluster. The validation experiments show that the relative performance of the different mediation mechanisms change for each cluster, which confirms that network-based metrics may be useful for mechanism selection in complex networks.

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