Learn More
The outcome of a legal dispute, namely, the decision of its adjudicator, is uncertain, and both parties develop their strategies on the basis of their appreciation of the probability that the adjudicator will accept their arguments or the arguments of their adversary. Costs and gains have to be balanced in light of this uncertainty in order to identify the(More)
Argumentation is modelled as a game where the payoffs are measured in terms of the probability that the claimed conclusion is, or is not, defeasibly provable, given a history of arguments that have actually been exchanged, and given the probability of the factual premises. The probability of a conclusion is calculated using a standard variant of Defeasible(More)
This paper proposes an approach to investigate norm-governed learning agents which combines a logic-based formalism with an equation-based counterpart. This dual formalism enables us to describe the reasoning of such agents and their interactions using argumentation, and, at the same time, to capture systemic features using equations. The approach is(More)
Towards neuro-argumentative agents based on the seamless integration of neural networks and defeasible formalisms, with principled probabilistic settings and along efficient algorithms , we investigate argumentative Boltzmann machines where the possible states of a Boltzmann machine are constrained by a prior argumentative knowledge. To make our ideas as(More)
We provide a conceptual analysis of several kinds of deadlines, represented in Temporal Modal Defeasible Logic. The paper presents a typology of deadlines, based on the following parameters: deontic operator, maintenance or achievement, presence or absence of sanctions, and persistence after the deadline. The deadline types are illustrated by a set of(More)
This paper proposes some variants of Temporal Defeasible Logic (TDL) to reason about normative modifications. These variants make it possible to differentiate cases in which, for example, modifications at some time change legal rules but their conclusions persist afterwards from cases where also their conclusions are blocked.
This paper provides a game-theoretical investigation on how to determine optimal strategies in dialogue games for argumentation. To make our ideas as widely applicable as possible, we adopt an abstract dialectical setting and model dialogues as extensive games with perfect information where optimal strategies are determined by preferences over outcomes of(More)