EDBT 2026 Demo / reviewers in the wild / expert
Jan Rudolf
dblp:335/1811
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 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.
| Artificial intelligence
1 paper |
Multi-agent systems · 50% Reinforcement learning · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Multi-agent systems
imperfect information games |
0.7 | 1 | 2023 | Value functions for depth-limited solving in zero-sum imperfect-information games · Artif. Intell. 2023 |
Machine learning › Reinforcement learning
value function |
0.7 | 1 | 2023 | Value functions for depth-limited solving in zero-sum imperfect-information games · Artif. Intell. 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Value functions for depth-limited solving in zero-sum imperfect-information games
Vojtech Kovarík, Dominik Seitz, Viliam Lisý, Jan Rudolf, Karel Ha |
Artif. Intell. | 4 |