Demo Data from EDBT 2026 / reviewers in the wild / expert
Anthony P. Leclerc
dblp:62/5626
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
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 · 93% Automated reasoning and model checking · 7% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Logic in computer science › logic programming
answer set programming |
0.3 | 1 | 2017 | On Computing World Views of Epistemic Logic Programs · IJCAI 2017 |
Logic in computer science › nonmonotonic reasoning
answer set solving |
0.3 | 1 | 2017 | On Computing World Views of Epistemic Logic Programs · IJCAI 2017 |
Logic in computer science › logic programming
epistemic logic programs |
0.3 | 1 | 2017 | On Computing World Views of Epistemic Logic Programs · IJCAI 2017 |
Logic in computer science
logic programming |
0.3 | 1 | 2017 | On Computing World Views of Epistemic Logic Programs · IJCAI 2017 |
Methods — techniques the papers use, named apart from their topics
multi-shot computation · 0.3goal-directed computing · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | On Computing World Views of Epistemic Logic ProgramsabstractThis paper presents a novel algorithm for computing world views of different semantics of epistemic logic programs (ELP) and two of its realization, called Ep-asp (for an older semantics) and Ep-asp^{se} (for the newest semantics), whose implementation builds on the theoretical advancement in the study of ELPs and takes advantage of the multi-shot computation paradigm of the answer set solver Clingo. The new algorithm differs from the majority of earlier algorithms in its strategy. Specifically, it computes one world view at a time and utilizes properties of world views to reduce its search space. It starts by computing an answer set and then determines whether or not a world view containing this answer set exists. In addition, it allows for the computation to focus on world views satisfying certain properties. The paper includes an experimental analysis of the performance of the two solvers comparing against a recently developed solver. It also contains an analysis of their performance in goal directed computing against a logic programming based conformant planning system, dlv-k. It concludes with some final remarks and discussion on the future work. Tran Cao Son, Tiep Le, Patrick Thor Kahl, Anthony P. Leclerc |
IJCAI | 4 |