Cooperatively learning mobile agents for gradient climbing

Jongeun Choi; Songhwai Oh; Roberto Horowitz

doi:10.1109/CDC.2007.4434061

Cooperatively learning mobile agents for gradient climbing

Jongeun Choi, Songhwai Oh, Roberto Horowitz

Department of Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Citations (Scopus)

Abstract

This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing. In particular, each sensing agent maintains its own smooth map which estimates the field. It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map. The proposed cooperatively learning control consists of motion coordination based on the recursive spatial estimation of an unknown field of interest with measurement noise. The convergence properties of the proposed coordination algorithm are analyzed using the ODE approach and verified by a simulation study.

Original language	English
Title of host publication	Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Pages	3139-3144
Number of pages	6
DOIs	https://doi.org/10.1109/CDC.2007.4434061
Publication status	Published - 2007
Event	46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States Duration: 2007 Dec 12 → 2007 Dec 14

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0191-2216

Other

Other	46th IEEE Conference on Decision and Control 2007, CDC
Country	United States
City	New Orleans, LA
Period	07/12/12 → 07/12/14

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modelling and Simulation
Control and Optimization

Access to Document

10.1109/CDC.2007.4434061

Fingerprint Dive into the research topics of 'Cooperatively learning mobile agents for gradient climbing'. Together they form a unique fingerprint.

Cite this

Choi, J., Oh, S., & Horowitz, R. (2007). Cooperatively learning mobile agents for gradient climbing. In Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC (pp. 3139-3144). [4434061] (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2007.4434061

@inproceedings{67b719b4b4514fc4a6d2a4fd5c306d1f,

title = "Cooperatively learning mobile agents for gradient climbing",

abstract = "This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing. In particular, each sensing agent maintains its own smooth map which estimates the field. It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map. The proposed cooperatively learning control consists of motion coordination based on the recursive spatial estimation of an unknown field of interest with measurement noise. The convergence properties of the proposed coordination algorithm are analyzed using the ODE approach and verified by a simulation study.",

author = "Jongeun Choi and Songhwai Oh and Roberto Horowitz",

year = "2007",

doi = "10.1109/CDC.2007.4434061",

language = "English",

isbn = "1424414989",

series = "Proceedings of the IEEE Conference on Decision and Control",

pages = "3139--3144",

booktitle = "Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC",

note = "46th IEEE Conference on Decision and Control 2007, CDC ; Conference date: 12-12-2007 Through 14-12-2007",

}

Choi, J, Oh, S & Horowitz, R 2007, Cooperatively learning mobile agents for gradient climbing. in Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC., 4434061, Proceedings of the IEEE Conference on Decision and Control, pp. 3139-3144, 46th IEEE Conference on Decision and Control 2007, CDC, New Orleans, LA, United States, 07/12/12. https://doi.org/10.1109/CDC.2007.4434061

TY - GEN

T1 - Cooperatively learning mobile agents for gradient climbing

AU - Choi, Jongeun

AU - Oh, Songhwai

AU - Horowitz, Roberto

PY - 2007

Y1 - 2007

N2 - This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing. In particular, each sensing agent maintains its own smooth map which estimates the field. It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map. The proposed cooperatively learning control consists of motion coordination based on the recursive spatial estimation of an unknown field of interest with measurement noise. The convergence properties of the proposed coordination algorithm are analyzed using the ODE approach and verified by a simulation study.

AB - This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing. In particular, each sensing agent maintains its own smooth map which estimates the field. It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map. The proposed cooperatively learning control consists of motion coordination based on the recursive spatial estimation of an unknown field of interest with measurement noise. The convergence properties of the proposed coordination algorithm are analyzed using the ODE approach and verified by a simulation study.

UR - http://www.scopus.com/inward/record.url?scp=52449124591&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=52449124591&partnerID=8YFLogxK

U2 - 10.1109/CDC.2007.4434061

DO - 10.1109/CDC.2007.4434061

M3 - Conference contribution

AN - SCOPUS:52449124591

SN - 1424414989

SN - 9781424414987

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 3139

EP - 3144

BT - Proceedings of the 46th IEEE Conference on Decision and Control 2007, CDC

T2 - 46th IEEE Conference on Decision and Control 2007, CDC

Y2 - 12 December 2007 through 14 December 2007

ER -