40 citations · 104 across the 14 of their papers we have counts for
15 papers
Comparison of SAT-based and ASP-based Algorithms for Inconsistency Measurement
Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo +1
We present algorithms based on satisfiability problem (SAT) solving, as well as answer set programming (ASP), for solving the problem of determining inconsistency degrees in propos…
Measuring Inconsistency in Declarative Process Specifications
Carl Corea, John Grant, Matthias Thimm
We address the problem of measuring inconsistency in declarative process specifications, with an emphasis on linear temporal logic on fixed traces (LTLff). As we will show, existin…
Revisiting initial sets in abstract argumentation
Matthias Thimm
We revisit the notion of initial sets by Xu and Cayrol, i.e., non-empty minimal admissible sets in abstract argumentation frameworks. Initial sets are a simple concept for analysin…
Fudge: A light-weight solver for abstract argumentation based on SAT reductions
Matthias Thimm, Federico Cerutti, Mauro Vallati
We present Fudge, an abstract argumentation solver that tightly integrates satisfiability solving technology to solve a series of abstract argumentation problems. While most of the…
Measuring Inconsistency over Sequences of Business Rule Cases
Carl Corea, Matthias Thimm, Patrick Delfmann
In this report, we investigate (element-based) inconsistency measures for multisets of business rule bases. Currently, related works allow to assess individual rule bases, however,…
Towards Ranking-based Semantics for Abstract Argumentation using Conditional Logic Semantics
Kenneth Skiba, Matthias Thimm
We propose a novel ranking-based semantics for Dung-style argumentation frameworks with the help of conditional logics. Using an intuitive translation for an argumentation framewor…
Towards Inconsistency Measurement in Business Rule Bases
Carl Corea, Matthias Thimm
We investigate the application of inconsistency measures to the problem of analysing business rule bases. Due to some intricacies of the domain of business rule bases, a straightfo…
Epistemic Graphs for Representing and Reasoning with Positive and Negative Influences of Arguments
Anthony Hunter, Sylwia Polberg, Matthias Thimm
This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up…
Proceedings of the Second Summer School on Argumentation: Computational and Linguistic Perspectives (SSA'16)
Sarah A. Gaggl, Matthias Thimm
This volume contains the thesis abstracts presented at the Second Summer School on Argumentation: Computational and Linguistic Perspectives (SSA'2016) held on September 8-12 in Pot…
System Descriptions of the First International Competition on Computational Models of Argumentation (ICCMA'15)
Matthias Thimm, Serena Villata
This volume contains the system description of the 18 solvers submitted to the First International Competition on Computational Models of Argumentation (ICCMA'15) and therefore giv…
Towards Large-scale Inconsistency Measurement
Matthias Thimm
We investigate the problem of inconsistency measurement on large knowledge bases by considering stream-based inconsistency measurement, i.e., we investigate inconsistency measures…
Probabilistic Argumentation with Epistemic Extensions and Incomplete Information
Anthony Hunter, Matthias Thimm
Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argu…
DecLiNe -- Models for Decay of Links in Networks
Julia Preusse, Jérôme Kunegis, Matthias Thimm +1
The prediction of graph evolution is an important and challenging problem in the analysis of networks and of the Web in particular. But while the appearance of new links is part of…
Stratified Labelings for Abstract Argumentation
Matthias Thimm, Gabriele Kern-Isberner
We introduce stratified labelings as a novel semantical approach to abstract argumentation frameworks. Compared to standard labelings, stratified labelings provide a more fine-grai…
Measuring Inconsistency in Probabilistic Knowledge Bases
Matthias Thimm
This paper develops an inconsistency measure on conditional probabilistic knowledge bases. The measure is based on fundamental principles for inconsistency measures and thus provid…