AI RESEARCH
Double Rectified Linear Unit-based Modular Semantics for Quantitative Bipolar Argumentation Framework
arXiv CS.AI
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ArXi:2605.02551v1 Announce Type: new Quantitative Bipolar Argumentation Frameworks (QBAFs) provide an alternative approach to computing argument acceptability in Bipolar Argumentation Frameworks (BAFs). Each argument is assigned an initial strength, which is then updated to a final strength by considering the influence of both its attackers and ers. Over the years, several semantics have been proposed to compute argument acceptability in QBAFs, yet they often yield divergent or counterintuitive results, even for simple acyclic cases. We.