We describe PADUA, a protocol designed to support two agents debating a classification by offering arguments based on association
rules mined from individual datasets. We motivate the style of argumentation supported by PADUA, and describe the protocol.
We discuss the strategies and tactics that can be employed by agents participating in a PADUA dialogue. PADUA is applied to
a typical problem in the classification of routine claims for a hypothetical welfare benefit. We particularly address the
problems that arise from the extensive number of misclassified examples typically found in such domains, where the high error
rate is a widely recognised problem. We give examples of the use of PADUA in this domain, and explore in particular the effect
of intermediate predicates. We have also done a large scale evaluation designed to test the effectiveness of using PADUA to
detect misclassified examples, and to provide a comparison with other classification systems.
Keywords Argumentation dialogue - Dialogue games - Classification - Association rules
This paper is a revised and consolidated version drawing on work presented at ECSQUARU 2007, COMMA 2008 (Wardeh et al. (2008). Arguments from experience: The PADUA protocol. Proceedings of COMputational models of argument, COMMA’2008, IOS press,
pp 405–416.) and JURIX 2008 (Wardeh et al. (2008). Argument based moderation of benefit assessment. Proceedings of JURIX’08 (21st international conference on legal knowledge
and information systems), pp 128–137).