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Multi-agent based classification using argumentation from experience

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Abstract

An approach to classification using a multi-agent system founded on an Argumentation from Experience paradigm is proposed. The technique is based on the idea that classification can be conducted as a process whereby a group of agents “argue” about the classification of a given case according to their experience as recorded in individual local data sets. The paper describes mechanisms whereby this can be achieved, which have been realised in the PISA framework. The framework allows both the possibility of agents operating in groups (coalitions) and migrating between groups. The proposed multi-agent classification using the Argumentation from Experience paradigm has been used to address standard, ordinal and unbalanced classification problems with good results. A full evaluation, in the context of these applications, is presented.

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Authors and Affiliations

  1. Department of Computer Science, The University of Liverpool, Liverpool, L69 3BX, UK

    Maya Wardeh, Frans Coenen & Trevor Bench-Capon

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  1. Maya Wardeh
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  2. Frans Coenen
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  3. Trevor Bench-Capon
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Correspondence to Frans Coenen.

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Wardeh, M., Coenen, F. & Bench-Capon, T. Multi-agent based classification using argumentation from experience. Auton Agent Multi-Agent Syst 25, 447–474 (2012). https://doi.org/10.1007/s10458-012-9197-6

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