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 :
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