Supervised self-organization of large homogeneous Swarms using Ergodic Projections of Markov Chains

Author

Chattopadhyay, Ishanu ; Ray, Asok

Author_Institution

Mech. Eng. Dept., Pennsylvania State Univ., University Park, PA, USA

fYear

2009

fDate

10-12 June 2009

Firstpage

2922

Lastpage

2927

Abstract

This paper formulates a self-organization algorithm to addresses the problem of emergent behavior supervision in engineered swarms of arbitrary population size. Based on collections of independent identical finite-state agents, the algorithm is derived to compute necessary perturbations in the local agents´ behavior, which guarantees convergence to the desired observed state of the swarm. A simulation example illustrates the underlying concept.

Keywords

Markov processes; discrete event systems; finite state machines; multi-robot systems; self-adjusting systems; Markov chains; ergodic projections; independent identical finite-state agents; large homogeneous swarms; supervised self-organization; Autonomous agents; Computational modeling; Discrete event systems; Eigenvalues and eigenfunctions; Mechanical engineering; Military computing; Mobile computing; Size control; Stochastic processes; Surveillance; Discrete Event Systems; Ergodic Projections; Finite State Ergodic Markov Chains; Swarms;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2009. ACC '09.

Conference_Location

St. Louis, MO

ISSN

0743-1619

Print_ISBN

978-1-4244-4523-3

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2009.5160372

Filename

5160372