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Various Artificial Intelligence semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. These semantics can make conflicting predictions, as in the situation known as floating reinstatement. We argue that the debate about which semantics makes the correct prediction can(More)
Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative(More)
Argumentation is now a very fertile area of research in Artificial Intelligence. Yet, most approaches to reasoning with arguments in AI are based on a normative perspective, relying on intuition as to what constitutes correct reasoning, sometimes aided by purpose-built hypothetical examples. For these models to be useful in agent-human argumentation, they(More)
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