Demo Data from EDBT 2026 / reviewers in the wild / expert
Ton Wessling
dblp:10/2079
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2006
—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 · 44% Reinforcement learning · 44% Representation and self-supervised learning · 13% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning › dynamic programming › value iteration
approximate value iteration |
0.1 | 1 | 2006 | Improving Approximate Value Iteration Using Memories and Predictive State Representations · AAAI 2006 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
search-based planning |
0.1 | 1 | 2006 | Improving Approximate Value Iteration Using Memories and Predictive State Representations · AAAI 2006 |
Machine learning › Representation and self-supervised learning › representation learning › latent representation learning › state representation learning
predictive state representation |
0.0 | 1 | 2006 | Improving Approximate Value Iteration Using Memories and Predictive State Representations · AAAI 2006 |
Methods — techniques the papers use, named apart from their topics
memory-based value iteration · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Improving Approximate Value Iteration Using Memories and Predictive State Representations
Michael R. James 0001, Ton Wessling, Nikos Vlassis |
AAAI | 2 |