EDBT 2026 Demo / reviewers in the wild / expert
Giovanni Buraglio
dblp:362/5217
· DBLP profile ↗
4ranked-venue papers
2as first author
4since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 2 first-author · 4 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 since 2021Theory of computation · 2 · 1 first-author · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Knowledge representation and reasoning · 94% Multi-agent systems · 6% | |
| Theoretical computer science
1 paper |
Algorithmic game theory and mechanism design · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
argumentation |
1.6 | 2 | 2025 | An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation · AAAI 2025 Justifying Argument Acceptance with Collective Attacks: Discussions and Disputes · IJCAI 2024 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › argumentation
abstract argumentation |
0.9 | 1 | 2025 | An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation · AAAI 2025 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › argumentation
ranking-based semantics |
0.9 | 1 | 2025 | An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation · AAAI 2025 |
Algorithmic game theory and mechanism design
social choice |
0.9 | 1 | 2025 | An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation · AAAI 2025 |
Methods — techniques the papers use, named apart from their topics
axiomatic characterization · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Splitting Argumentation Frameworks with Collective Attacks and SupportsabstractThis work proposes novel splitting techniques for argumentation formalisms that incorporate supports between defeasible elements. We base our studies on Bipolar Set-Based Argumentation Frameworks (BSAFs), which generalize argumentation frameworks with collective attacks (SETAFs), as well as Bipolar Argumentation Frameworks (BAFs), by incorporating both collective attacks and supports. Notably, BSAFs establish a crucial link to structured argumentation as they naturally capture general (potentially non-flat) assumption-based argumentation. The increase in expressiveness calls for diverse forms of splitting. We consider splits over collective attacks (thereby generalizing the recently proposed splitting techniques for SETAFs), splits over collective supports, as well as splits over both collective attacks and supports. We establish suitable splitting schemata and prove their correctness for the most common argumentation semantics. Matti Berthold, Lydia Blümel, Giovanni Buraglio, Anna Rapberger |
KR | 3 |
| 2026 | Splitting Assumption-Based Argumentation FrameworksabstractAssumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. However, the high computational complexity of core reasoning tasks in ABA poses a significant challenge for its applicability. This issue is further aggravated when ABA frameworks (ABAFs) are instantiated into graph-based argumentation formalisms, such as Dung's Argumentation Frameworks (AFs) and Argumentation Frameworks with Collective Attacks (SETAFs). In knowledge representation and reasoning, a key strategy to address computational intractability is to optimise reasoning over a given knowledge base through divide-and-conquer algorithms. A paradigmatic example of this approach is splitting, where extensions of a given framework are computed incrementally, by restricting the search space to sub-frameworks only, and then combining the obtained results. This approach has been successfully applied to AFs, for which also a parametrised version has been introduced under stable semantics. However, the exponential growth produced by the instantiation might undermine the usefulness of splitting on the argument graphs induced by ABAFs. To address this issue, our work investigates the concept of splitting on the knowledge base rather than on its graph-based instantiation. Furthermore, we generalise splitting to its parametrised version for ABAFs. Giovanni Buraglio, Wolfgang Dvorák, Stefan Woltran |
KR | 1 |
| 2025 | An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract ArgumentationabstractIn this paper, we introduce a new family of argument-ranking semantics which can be seen as a refinement of the classification of arguments into skeptically accepted, credulously accepted and rejected. To this end we use so-called social ranking functions which have been developed recently to rank individuals based on their performance in groups. We provide necessary and sufficient conditions for a social ranking function to give rise to an argument-ranking semantics satisfying the desired refinement property. Lars Bengel, Giovanni Buraglio, Jan Maly 0001, Kenneth Skiba |
AAAI | 2 |
| 2024 | Justifying Argument Acceptance with Collective Attacks: Discussions and Disputes
Giovanni Buraglio, Wolfgang Dvorák, Matthias König 0002, Markus Ulbricht 0001 |
IJCAI | 1 |