Name
Abstract | ||
|---|---|---|
In this paper, we present the first stage of our research strategy to develop an immune-inspired solution for detecting anomalies in a foraging swarm robotic system with an immuno-engineering approach. Within immuno-engineering, the initial stage of our research involves the understanding of problem domain, namely anomaly detection, in a foraging swarm robotic system deployed in dynamic environments. We present a systematically derived set of activities for this stage derived with Goal Structuring Notation and results of experiments carried out to establish the time-varying behaviour and how anomalies manifest themselves. Our future work will then be used to select and tailor an appropriate AIS algorithm to provide an effective and efficient means of anomaly detection. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-03246-2_16 | ICARIS |
Keywords | Field | DocType |
research strategy,anomaly detection,swarm robotics,goal structuring notation,initial stage,foraging swarm,appropriate ais algorithm,robotic system,dynamic environment,immuno-engineering approach,efficient mean | Robotic systems,Anomaly detection,Notation,Swarm behaviour,Problem domain,Computer science,Artificial intelligence,Structuring,Foraging,Machine learning,Swarm robotics | Conference |
Volume | ISSN | Citations |
5666 | 0302-9743 | 2 |
PageRank | References | Authors |
0.40 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| HuiKeng Lau | 1 | 23 | 5.43 |
| Iain Bate | 2 | 469 | 58.87 |
| Jon Timmis | 3 | 1237 | 120.32 |