This paper seeks to better understand the links between human reasoning and preferred extensions as found within formal argumentation, especially in the context of uncertainty. The degree of believability of a conclusion may be associated with the number of preferred extensions in which the conclusion is credulously accepted. We are interested in whether people agree with this evaluation. A set of experiments with human participants is presented to investigate the validity of such an association. Our results show that people tend to agree with the outcome of a version of Thimm’s probabilistic semantics in purely qualitative domains as well as in domains in which conclusions express event likelihood. Furthermore, we are able to characterise ...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In traditional tasks of formal reasoning, participants are asked to evaluate the validity of logical...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
The debate over what counts as credible evidence often occurs on a methodological level (i.e., about...
peer reviewedAccording to the Argumentative Theory, human reasoning has an argumentative function, w...
AbstractMany works in the past showed that human judgments of uncertainty do not conform very well t...
One of the main objectives of AI is modelling human reasoning. Since preference information is an in...
We address the problem of deciding skeptical acceptance wrt. preferred semantics of an argument in a...
Abstract. Abstract argumentation offers an appealing way of representing and evaluating arguments an...
This paper offers a probabilistic treatment of the conditions for argument cogency as endorsed in in...
Combining computational models of argumentation with probability theory has recently gained increasi...
The relation between probabilistic and explanatory reasoning is a classical topic in philosophy of s...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In traditional tasks of formal reasoning, participants are asked to evaluate the validity of logical...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
This paper seeks to better understand the links between human reasoning and preferred extensions as ...
The debate over what counts as credible evidence often occurs on a methodological level (i.e., about...
peer reviewedAccording to the Argumentative Theory, human reasoning has an argumentative function, w...
AbstractMany works in the past showed that human judgments of uncertainty do not conform very well t...
One of the main objectives of AI is modelling human reasoning. Since preference information is an in...
We address the problem of deciding skeptical acceptance wrt. preferred semantics of an argument in a...
Abstract. Abstract argumentation offers an appealing way of representing and evaluating arguments an...
This paper offers a probabilistic treatment of the conditions for argument cogency as endorsed in in...
Combining computational models of argumentation with probability theory has recently gained increasi...
The relation between probabilistic and explanatory reasoning is a classical topic in philosophy of s...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In traditional tasks of formal reasoning, participants are asked to evaluate the validity of logical...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...