EDBT 2026 Demo / reviewers in the wild / expert
Mance E. Harmon
dblp:33/2729
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 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
2 papers |
Reinforcement learning · 53% Deep learning architectures and training · 27% Motion planning and robot control · 20% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning › value-based reinforcement learning
q-learning |
0.0 | 1 | 1996 | Residual Q-Learning Applied to Visual Attention · ICML 1996 |
Machine learning › Reinforcement learning › value-based reinforcement learning
residual q-learning |
0.0 | 1 | 1996 | Residual Q-Learning Applied to Visual Attention · ICML 1996 |
Machine learning › Deep learning architectures and training › attention mechanism
visual attention |
0.0 | 1 | 1996 | Residual Q-Learning Applied to Visual Attention · ICML 1996 |
Robotics › Motion planning and robot control › robot control › optimization-based control
differential game |
0.0 | 1 | 1994 | Advantage Updating Applied to a Differrential Game · NIPS 1994 |
Methods — techniques the papers use, named apart from their topics
q-learning · 0.0advantage updating · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Residual Q-Learning Applied to Visual Attention
Cesar Bandera, Francisco J. Vico, José Manuel Bravo, Mance E. Harmon, Leemon Baird |
ICML | 4 |
| 1994 | Advantage Updating Applied to a Differrential Game
Mance E. Harmon, Leemon Baird, A. Harry Klopf |
NIPS | 1 |