Title:
Geometric Foraging Strategies in Multi-Agent Systems Based on Biological Models

dc.contributor.author Haque, Musad A.
dc.contributor.author Rahmani, Amir R.
dc.contributor.author Egerstedt, Magnus B.
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.date.accessioned 2011-04-18T17:52:36Z
dc.date.available 2011-04-18T17:52:36Z
dc.date.issued 2010-12
dc.description (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. en_US
dc.description Digital Object Identifier : 10.1109/CDC.2010.5717805
dc.description.abstract In nature, communal hunting is often performed by predators by charging through an aggregation of prey. However, it has been noticed that variations exist in the geometric shape of the charging front; in addition, distinct differences arise between the shapes depending on the particulars of the feeding strategy. For example, each member of a dolphin foraging group must contribute to the hunt and will only be able to eat what it catches. On the other hand, some lions earn a "free lunch" by feigning help and later feasting on the prey caught by the more skilled hunters in the foraging group. We model the charging front of the predators as a curve moving through a prey density modeled as a reaction-diffusion process and we optimize the shape of the charging front in both the free lunch and no-free-lunch cases. These different situations are simulated under a number of varied types of predator-prey interaction models, and connections are made to multi-agent robot systems. en_US
dc.identifier.citation M. Haque, A. Rahmani, and M. Egerstedt. Geometric Foraging Strategies in Multi-Agent Systems Based on Biological Models. IEEE Conference on Decision and Control, Atlanta, GA, Dec. 2010. en_US
dc.identifier.issn 0743-1546
dc.identifier.uri http://hdl.handle.net/1853/38571
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers
dc.subject Multi-agent systems en_US
dc.subject Biological models en_US
dc.subject Predator-prey systems en_US
dc.title Geometric Foraging Strategies in Multi-Agent Systems Based on Biological Models en_US
dc.type Text
dc.type.genre Article
dc.type.genre Proceedings
dspace.entity.type Publication
local.contributor.author Egerstedt, Magnus B.
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
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relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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