In this paper, the problem of deriving sensible information from a collection of argumentation
systems coming from different agents is addressed. The underlying argumentation theory is …

Cardinal scores (numeric ratings) collected from people are well known to suffer from
miscalibrations. A popular approach to address this issue is to assume simplistic models of …

Belief merging is often described as the process of defining a base which best represents
the beliefs of a group of agents (a profile of belief bases). The resulting base can be viewed …

This chapter focuses on the dynamics of information represented in logical or numerical
formats, from pioneering works to recent developments. The logical approach to belief …

In the last decade, several approaches have been proposed for merging multiple and
potentially conflicting pieces of information. Egalitarian fusion modes pick solutions that …

When merging belief sets from different agents, the result is normally a consistent belief set
in which the inconsistency between the original sources is not represented. As probability …

Real-world automated reasoning systems must contend with inconsistencies and the vast
amount of information stored in relational databases. In this paper, we introduce compilation …

This short paper studies the problem of merging of different independent data sources linked
to a lightweight ontology under the incommensurability assumption. In general, data are …

Modern web forms interact with the user in real-time by detecting errors and filling-in implied
values, which in terms of automated reasoning amounts to SAT solving and theorem …

Merging operators aim at defining the beliefs (resp. the goal) of a group of agents from a
profile of bases, gathering the beliefs (resp. the goals) of each member of the group. In the …