Demo Data from EDBT 2026 / reviewers in the wild / expert
Anas El Kouaiti
dblp:376/8221
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-author · 2 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 |
Planning, search and constraint satisfaction · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Smart cities and intelligent transportation · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › plan representation › planning languages
PDDL+ |
0.8 | 1 | 2024 | PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation · ICAPS 2024 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
plan representation |
0.8 | 1 | 2024 | PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation · ICAPS 2024 |
Smart cities and intelligent transportation › traffic control
traffic signal optimization |
0.2 | 1 | 2024 | PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation · ICAPS 2024 |
Methods — techniques the papers use, named apart from their topics
heuristic search · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | PDDL+ Models for Deployable yet Effective Traffic Signal OptimisationabstractThe use of planning techniques in traffic signal optimisation has proven effective in managing unexpected traffic conditions as well as typical traffic patterns. However, significant challenges concerning the deployability of generated signal strategies remain, as existing approaches tend not to consider constraints and features of the actual real-world infrastructure on which they will be implemented. To address this challenge, we introduce a range of PDDL+ models embodying technological requirements as well as insights from domain experts. The proposed models have been extensively tested on historical data using a range of well-known search strategies and heuristics, as well as alternative encodings. Results demonstrate their competitiveness with the state of the art. Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Thomas Leo McCluskey, Mauro Vallati |
ICAPS | 1 |
| 2024 | Deployable Yet Effective Traffic Signal Optimisation via Automated Planning (Extended Abstract)abstractThe use of planning techniques in traffic signal optimisation has proven effective in managing unexpected traffic conditions as well as typical traffic patterns. However, significant challenges concerning the deployability of generated signal plans remain, as planning systems need to consider constraints and features of the actual real-world infrastructure on which they will be implemented. To address this challenge, we introduce a range of PDDL+ models embodying technological requirements as well as insights from domain experts. The proposed models have been extensively tested on historical data using a range of well-known search strategies and heuristics, as well as alternative encodings. Results demonstrate their competitiveness with the state of the art. Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Thomas Leo McCluskey, Mauro Vallati |
SOCS | 1 |