DocumentCode
10399
Title
Efficient Foraging Strategies in Multi-Agent Systems Through Curve Evolutions
Author
Haque, Md ; Rahmani, Amine ; Egerstedt, M. ; Yezzi, Anthony
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
59
Issue
4
fYear
2014
fDate
Apr-14
Firstpage
1036
Lastpage
1041
Abstract
In nature, communal hunting is often performed by predators charging through an aggregation of prey. Variations exist in the geometric shape of the charging front depending on the particulars of the feeding strategy. Inspired by biology, this technical note investigates these geometric variations, and we model the predator front as a curve moving through a prey density. Using variational arguments for evolving the curve shape, we optimize the shape of the front.
Keywords
curve fitting; evolutionary computation; multi-agent systems; predator-prey systems; biology; communal hunting; curve evolution; feeding strategy; foraging strategy; geometric shape; geometric variation; multiagent system; predator front; prey density; Biological system modeling; Evolution (biology); Mathematical model; Multi-agent systems; Predator prey systems; Shape; Bio-inspired methods; curve evolutions; multi-agent foraging;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2013.2281877
Filename
6600892
Link To Document