Name
Title | ||
|---|---|---|
Applying Scale-Invariant Dynamics to Improve Consensus Achievement of Agents in Motion. |
Abstract | ||
|---|---|---|
In order to efficiently execute tasks, autonomous collective systems are required to rapidly reach accurate consensus, no matter how the group is distributed over the environment. Finding consensus in a group of agents that are in motion is a particularly great challenge, especially at larger scales and extensive environments. Nevertheless, numerous collective systems in nature reach consensus independently of scale, i.e. they are scale-free or scale-invariant. Inspired by these natural phenomena, the aim of our work is to improve consensus achievement in artificial systems by finding fundamental links between individual decision-making and scale-free collective behavior. For model validation we use physics-based simulations as well as a swarm robotic testbed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-99608-0_42 | DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Consensus achievement,Scale invariance Swarm robotics | Collective behavior,Scale invariance,Swarm behaviour,Computer science,Testbed,Artificial intelligence,Artificial systems,Machine learning,Swarm robotics | Conference |
Volume | ISSN | Citations |
801 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ilja Rausch | 1 | 0 | 0.34 |
| Yara Khaluf | 2 | 42 | 8.79 |
| Pieter Simoens | 3 | 511 | 47.30 |