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Technical Briefs

On the Number of Informed Agents and Their Initial Positions in a Free Flocking

[+] Author and Article Information
Mohammad Haeri

e-mail: haeri@sina.sharif.edu
Advanced Control Systems Lab,
Electrical Engineering Department,
Sharif University of Technology,
Tehran 11155-4363, Iran

Contributed by Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT AND CONTROL. Manuscript received March 22, 2011; final manuscript received March 16, 2013; published online May 29, 2013. Assoc. Editor: Qian Wang.

J. Dyn. Sys., Meas., Control 135(5), 054501 (May 29, 2013) (7 pages) Paper No: DS-11-1082; doi: 10.1115/1.4024172 History: Received March 22, 2011; Revised March 16, 2013

In a multi-agent system, the number and initial position of informed agents play a major role in the convergence of uninformed agents. In this paper, three different patterns of informed agents' initial positions are studied to see how the convergence percentage can be affected by the number of informed agents. The proposed initial locations are intuitive and inferred from the collective behavior in humans. To evaluate efficiency of the proposed methods and to compare them from different points of view, large number of computer simulations is performed and results are analyzed.

Copyright © 2013 by ASME
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Figures

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Fig. 1

The desired square

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Fig. 7

Number of informed agents with respect to xr and for different σ

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Fig. 5

Number of informed agents with respect to σ and four different p

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Fig. 6

Number of informed agents with respect to σ and four different xr

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Fig. 2

Initial positions of the informed agents in the square configuration

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Fig. 3

Initial positions of the informed agents in the circle configuration

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Fig. 4

Initial positions of the informed agents in the triangle configuration

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Fig. 8

Percentage of converged uninformed agents

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Fig. 9

Percentage of converged uninformed agents

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Fig. 10

Percentage of converged uninformed agents for different values of xr

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Fig. 11

Time required for forming a quasi-flock for different values of nu

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Fig. 14

Convergence time for different number of uninformed agents nu

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Fig. 15

Convergence time for different values of p

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Fig. 16

Convergence time for different values of xr

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Fig. 12

Time needed for forming a quasi-flock for different values of p

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Fig. 13

Time for forming a quasi-flock for different values of xr

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