Demo Data from EDBT 2026 / reviewers in the wild / expert
Brent Beer
dblp:52/8399
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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 |
Multi-agent systems · 67% Motion planning and robot control · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › multi-robot control
distributed robot control |
0.1 | 1 | 2010 | A Distributed Method for Evaluating Properties of a Robot Formation · AAAI 2010 |
Knowledge, reasoning and agents › Multi-agent systems
multi-robot systems |
0.1 | 1 | 2010 | A Distributed Method for Evaluating Properties of a Robot Formation · AAAI 2010 |
Knowledge, reasoning and agents › Multi-agent systems › multi-robot systems
robot formation control |
0.1 | 1 | 2010 | A Distributed Method for Evaluating Properties of a Robot Formation · AAAI 2010 |
Methods — techniques the papers use, named apart from their topics
distributed evaluation of formation properties · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | A Distributed Method for Evaluating Properties of a Robot FormationabstractAs a robot formation increases in size or explores places where it is difficult for a human operator to interact, autonomous control becomes critical. We propose a distributed autonomous method for evaluating properties of multi-robot systems, and then discuss how this information can be applied to improve performance with respect to a given operation. We present this as an extension of our previous work on robot formations; however, the techniques described could be adapted to other multi-robot systems. Brent Beer, Ross Mead, Jerry B. Weinberg |
AAAI | 1 |