Demo Data from EDBT 2026 / reviewers in the wild / expert
Dang-Vien Tran
dblp:14/2111
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Software engineering, systems software and programming languages · 1 · 1 first-authorGraphics, 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.
| Artificial intelligence
1 paper |
Planning, search and constraint satisfaction · 100% | |
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › nondeterministic planning
conformant planning |
0.1 | 1 | 2011 | On Improving Conformant Planners by Analyzing Domain-Structures · AAAI 2011 |
Methods — techniques the papers use, named apart from their topics
stratification · 0.2landmark detection · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | On Improving Conformant Planners by Analyzing Domain-StructuresabstractThe paper introduces a novel technique for improving the performance and scalability of best-first progression-based conformant planners. The technique is inspired by different well-known techniques from classical planning, such as landmark and stratification. Its most salient feature is that it is relatively cheap to implement yet quite effective when applicable. The effectiveness of the proposed technique is demonstrated by the development of new conformant planners by integrating the technique in various state-of-the-art conformant planners and an extensive experimental evaluation of the new planners using benchmarks collected from various sources. The result shows that the technique can be applied in several benchmarks and helps improve both performance and scalability of conformant planners. Hoang-Khoi Nguyen, Dang-Vien Tran, Tran Cao Son, Enrico Pontelli |
AAAI | 2 |
| 2009 | Improving Performance of Conformant Planners: Static Analysis of Declarative Planning Domain Specifications
Dang-Vien Tran, Hoang-Khoi Nguyen, Enrico Pontelli, Tran Cao Son |
PADL | 1 |