Demo Data from EDBT 2026 / reviewers in the wild / expert
Byung-Do Kim
dblp:53/7953
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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.
| Artificial intelligence
1 paper |
Planning, search and constraint satisfaction · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning
strategy planning |
0.3 | 1 | 2018 | Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of Curling · IJCAI 2018 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of CurlingabstractMost artificial intelligence (AI) based learning systems act in virtual or laboratory environments. Here we demonstrate an AI-based curling robot system named `Curly' that competes on a real-world curling ice sheet. Curly encompasses (1) an AI-based curling strategy and simulation engine under consideration of the high `icy' uncertainty, (2) the thrower robot enabled by autonomous driving with traction control, and (3) the skip robot that allows to recognize the curling field and stone configuration based on vision technology. The Curly performed well both: in classical game situations and when interacting with human opponents, namely, the top-ranked Korean amateur high school curling team. Dong-Ok Won, Byung-Do Kim, Ho-Jung Kim, Tae-San Eom, Klaus-Robert Müller, Seong-Whan Lee |
IJCAI | 2 |