Name
Title | ||
|---|---|---|
Disentangling Automatic And Semi-Automatic Approaches To The Optimization-Based Design Of Control Software For Robot Swarms |
Abstract | ||
|---|---|---|
Optimization-based design is an effective and promising approach to realizing collective behaviours for robot swarms. Unfortunately, the domain literature often remains vague about the exact role played by the human designer, if any. It is our contention that two cases should be disentangled: semi-automatic design, in which a human designer operates and steers an optimization process (for example, by fine-tuning the parameters of the optimization algorithm); and (fully) automatic design, in which the optimization process does not involve, need or allow any human intervention. In this Perspective, we briefly review the relevant literature; illustrate the hypotheses, characteristics and core challenges of semi-automatic and automatic design; and sketch out the context in which they could be ideally applied.Developing swarm robots for a specific application is a time consuming process and can be alleviated by automated optimization of the behaviour. Birattari and colleagues discuss that there are two fundamentally different design approaches; a semi-autonomous one, which allows for situation specific tuning from human engineers and one that needs to be entirely autonomous. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1038/s42256-020-0215-0 | NATURE MACHINE INTELLIGENCE |
DocType | Volume | Issue |
Journal | 2 | 9 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mauro Birattari | 1 | 2021 | 146.61 |
| Antoine Ligot | 2 | 5 | 2.45 |
| Ken Hasselmann | 3 | 3 | 0.74 |