Name
Title | ||
|---|---|---|
Brain Emotional Learning-Based Intelligent Controller For Flocking Of Multi-Agent Systems |
Abstract | ||
|---|---|---|
A biologically-inspired intelligent controller based on a computational model of emotional learning in mammal's brain is employed for flocking control of Multi-Agent Systems (MAS). The methodology, known as Brain Emotional Learning Based Intelligent Controller (BELBIC),is implemented in this application for the first time, enhancing the flocking strategy with multi-objective properties. The learning capabilities added by BELBIC to the flocking are very useful, especially when dealing with noises and/or system uncertainty. Furthermore, the low computational complexity of the proposed method makes it very promising for implementation in real-time applications. Numerical results of the BELBIC-based flocking for MAS demonstrate the effectiveness of the proposed approach. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 AMERICAN CONTROL CONFERENCE (ACC) | BELBIC,Flocking (texture),Control theory,Computer science,Social emotional learning,Control engineering,Multi-agent system,Artificial intelligence,Computational complexity theory |
DocType | ISSN | Citations |
Conference | 0743-1619 | 2 |
PageRank | References | Authors |
0.36 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Jafari | 1 | 32 | 6.11 |
| Hao Xu | 2 | 19 | 4.19 |
| Luis Rodolfo García Carrillo | 3 | 11 | 4.74 |