Abstract
An approach to multi-agent classification, using an Argumentation from Experience paradigm is describe, whereby individual agents argue for a given example to be classified with a particular label according to their local data. Arguments are expressed in the form of classification rules which are generated dynamically. The advocated argumentation process has been implemented in the PISA multi-agent framework, which is also described. Experiments indicate that the operation of PISA is comparable with other classification approaches and that it can be utilised for Ordinal Classification and Imbalanced Class problems.
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Wardeh, M., Coenen, F., Bench-Capon, T., Wyner, A. (2011). Multi-agent Based Classification Using Argumentation from Experience. In: Huang, J.Z., Cao, L., Srivastava, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 6635. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20847-8_30
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DOI: https://doi.org/10.1007/978-3-642-20847-8_30
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