Jenny Eriksson Lundström

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In this paper we show how to capture dialogue games in Defeasible Logic. We argue that Defeasible Logic is a natural candidate and general representation formalism to capture dialogue games even with requirements more complex than existing formalisms for this kind of games. We parse the dialogue into defeasible rules with time of the dialogue as time of the(More)
Agent interactions where the agents hold conflicting goals could be modelled as adversarial argumentation games. In many real-life situations (e.g., criminal litigation, consumer legislation), due to ethical, moral or other principles governing interaction, the burden of proof, i.e., which party is to lose if the evidence is balanced [21], is a priori fixed(More)
In legal settings the admissibility of any speech act could be contested (cf. rule-scepticism, a view of legal positivism [5]). Thus all arguments, including rules, should initially be considered unascertained as to their acceptability and meaning for a given legal dispute. Only after considering the circumstances of the particular dispute, either(More)
Automated decision-making is a significant concern for the AI community and especially for multi-agent systems. Although it has long been known among scholars of rhetoric that human decision-making can be systematically influenced by skillful argumentation, there seems to be a lack of formalizations which handle the impact rhetoric has on the concealment of(More)
Approach An approach to logical analysis and formalization of argumentation and dispute as game trees, using a metalogic defeasible framework. Formalization of the interplay between the logical layer of defeasible argumentation and the dynamic progression in the argumentation. Draws on analogies between tactical chess game notions and notions in adversarial(More)
When learning problem-solving or decision-making strategies, a human needs to be active and develop an own mental model of the problem-domain. To optimise the learned knowledge, clear, timely and individually adapted comments on the own findings are needed. In a computerised learning environment, the adaptation to the user is a complex task, often handled(More)