Demo Data from EDBT 2026 / reviewers in the wild / expert
Michal Sochanski
dblp:220/9790
· DBLP profile ↗
4ranked-venue papers
4as first author
2since 2021 · last 2026
0000-0002-6888-3407ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 4 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 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.
| Theoretical computer science
1 paper |
Logic in computer science · 50% Automated reasoning and model checking · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Logic in computer science › formal semantics
definite descriptions |
1.0 | 1 | 2026 | Description Logics with Two Types of Definite Descriptions: Complexity, Expressiveness, and Automated Deduction · AAAI 2026 |
Logic in computer science › knowledge representation and reasoning
description logic |
1.0 | 1 | 2026 | Description Logics with Two Types of Definite Descriptions: Complexity, Expressiveness, and Automated Deduction · AAAI 2026 |
Automated reasoning and model checking
satisfiability |
1.0 | 1 | 2026 | Description Logics with Two Types of Definite Descriptions: Complexity, Expressiveness, and Automated Deduction · AAAI 2026 |
Automated reasoning and model checking › decision procedures
tableau decision procedure |
1.0 | 1 | 2026 | Description Logics with Two Types of Definite Descriptions: Complexity, Expressiveness, and Automated Deduction · AAAI 2026 |
Methods — techniques the papers use, named apart from their topics
tableau method · 1.0bisimulation · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Description Logics with Two Types of Definite Descriptions: Complexity, Expressiveness, and Automated DeductionabstractDefinite descriptions are expressions of the form „the unique x satisfying property C,” which allow reference to objects through their distinguishing characteristics. They play a crucial role in ontology and query languages, offering an alternative to proper names (IDs), which lack semantic content and serve merely as placeholders. In this paper, we introduce two extensions of the well-known description logic ALC with local and global definite descriptions, denoted ALCiL and ALCiG, respectively. We define appropriate bisimulation notions for these logics, enabling an analysis of their expressiveness. We show that although both logics share the same tight ExpTime complexity bounds for concept and ontology satisfiability, ALCiG is strictly more expressive than ALCiL. Moreover, we present tableau-based decision procedures for satisfiability in both logics, provide their implementation, and report on a series of experiments. The empirical results demonstrate the practical utility of the implementation and reveal interesting correlations between performance and structural properties of the input formulas. Michal Sochanski, Przemyslaw Andrzej Walega, Michal Zawidzki |
AAAI | 1 |
| 2022 | Representing Formulas of Propositional Logic by Cographs, Permutations and Tables
Michal Sochanski |
Diagrams | 1 |
| 2020 | Experimenting with Diagrams in Mathematics
Michal Sochanski |
Diagrams | 1 |
| 2018 | Interpreting Diagrammatic Reasoning - Between Empiricism and Realism
Michal Sochanski |
Diagrams | 1 |