EDBT 2026 Demo / reviewers in the wild / expert
Wiktor Mateusz Piotrowski
dblp:178/8571
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 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 |
Planning, search and constraint satisfaction · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
heuristic search |
0.2 | 1 | 2016 | Heuristic Planning for Hybrid Systems · AAAI 2016 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › heuristic search
heuristic search planning |
0.2 | 1 | 2016 | Heuristic Planning for PDDL+ Domains · IJCAI 2016 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning › hybrid planning
mixed discrete-continuous planning |
0.2 | 1 | 2016 | Heuristic Planning for Hybrid Systems · AAAI 2016 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › plan representation › planning languages
PDDL+ |
0.2 | 1 | 2016 | Heuristic Planning for PDDL+ Domains · IJCAI 2016 |
Methods — techniques the papers use, named apart from their topics
discretise and validate · 0.2SRPG+ heuristic · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Heuristic Planning for Hybrid SystemsabstractPlanning in hybrid systems has been gaining research interest in the Artificial Intelligence community in recent years. Hybrid systems allow for a more accurate representation of real world problems, though solving them is very challenging due to complex system dynamics and a large model feature set. We developed DiNo, a new planner designed to tackle problems set in hybrid domains.DiNo is based on the discretise and validate approach and uses the novel Staged Relaxed Planning Graph+ (SRPG+) heuristic. Wiktor Mateusz Piotrowski, Maria Fox 0001, Derek Long, Daniele Magazzeni, Fabio Mercorio |
AAAI | 1 |
| 2016 | Heuristic Planning for PDDL+ Domains
Wiktor Mateusz Piotrowski, Maria Fox 0001, Derek Long, Daniele Magazzeni, Fabio Mercorio |
IJCAI | 1 |