Abstract
This paper addresses the problem of exploring how organizational structures may evolve over time using the information from the agents’ trust models. We present a mechanism based on clustering techniques capable of detecting behavioural patterns in organizational multi-agent systems, thereby identifying new roles that dynamically extend the role taxonomy. We present experimental results showing that this extension leads to an improvement of the agents’ decision making processes when compared to static organizational structures.
student paper. The present work has been partially funded by the Spanish Ministry of Education and Science under project TIN2006-14630-C03-02 and by the Spanish project “Agreement Technologies” (CONSOLIDER CSD2007-0022, INGENIO 2010).
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Hermoso, R., Billhardt, H., Ossowski, S. (2009). Dynamic Evolution of Role Taxonomies through Multidimensional Clustering in Multiagent Organizations. In: Yang, JJ., Yokoo, M., Ito, T., Jin, Z., Scerri, P. (eds) Principles of Practice in Multi-Agent Systems. PRIMA 2009. Lecture Notes in Computer Science(), vol 5925. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11161-7_45
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DOI: https://doi.org/10.1007/978-3-642-11161-7_45
Publisher Name: Springer, Berlin, Heidelberg
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