Resolving Conflicting Arguments under Uncertainties
This work addresses the challenge of handling uncertainties and conflicts in open-domain distributed knowledge applications, which is an incremental contribution to argumentation theory.
The paper tackles the problem of drawing useful conclusions from uncertain and incomplete common sense information in distributed knowledge applications by proposing an integrated framework that extends definite argumentation theory to model uncertainty and supports three views over conflicting knowledge.
Distributed knowledge based applications in open domain rely on common sense information which is bound to be uncertain and incomplete. To draw the useful conclusions from ambiguous data, one must address uncertainties and conflicts incurred in a holistic view. No integrated frameworks are viable without an in-depth analysis of conflicts incurred by uncertainties. In this paper, we give such an analysis and based on the result, propose an integrated framework. Our framework extends definite argumentation theory to model uncertainty. It supports three views over conflicting and uncertain knowledge. Thus, knowledge engineers can draw different conclusions depending on the application context (i.e. view). We also give an illustrative example on strategical decision support to show the practical usefulness of our framework.