EDBT 2026 Demo / reviewers in the wild / expert
Alessandro Arsie
dblp:14/2520
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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 |
Multi-agent systems · 56% Robot navigation and mapping · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
coverage control |
0.1 | 1 | 2009 | Equitable partitioning policies for robotic networks · ICRA 2009 |
Knowledge, reasoning and agents › Multi-agent systems
multi-robot systems |
0.1 | 1 | 2009 | Equitable partitioning policies for robotic networks · ICRA 2009 |
Knowledge, reasoning and agents › Multi-agent systems
distributed algorithms |
0.0 | 1 | 2009 | Equitable partitioning policies for robotic networks · ICRA 2009 |
Methods — techniques the papers use, named apart from their topics
power diagram · 0.1lloyd algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Equitable partitioning policies for robotic networksabstractThe most widely applied resource allocation strategy is to balance, or equalize, the total workload assigned to each resource. In mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and subregions, and (iii) each agent is responsible for service requests originating within its own subregion. In this paper, we provide the first distributed algorithm that provably allows m agents to converge to an equitable partition of the workspace, from any initial configuration, i.e., globally. Our approach is related to the classic Lloyd algorithm, and provides novel insights into the properties of power diagrams. Simulation results are presented and discussed. Marco Pavone 0001, Alessandro Arsie, Emilio Frazzoli, Francesco Bullo |
ICRA | 2 |