TY - JOUR
T1 - Supervised self-organization of homogeneous swarms using ergodic projections of markov chains
AU - Chattopadhyay, I.
AU - Ray, A.
N1 - Funding Information:
Manuscript received May 21, 2008; revised October 31, 2008 and March 10, 2009. First published May 15, 2009; current version published November 18, 2009. This work was supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office (ARO) under Grant W911NF-07-1-0376, by the U.S. Office of Naval Research under Grant N00014-08-1-380, and by the National Aeronautics and Space Administration (NASA) under Cooperative Agreement NNX07AK49A. This paper was recommended by Associate Editor R. Selmic.
PY - 2009
Y1 - 2009
N2 - This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.
AB - This paper formulates a self-organization algorithm to address the problem of global behavior supervision in engineered swarms of arbitrarily large population sizes. The swarms considered in this paper are assumed to be homogeneous collections of independent identical finite-state agents, each of which is modeled by an irreducible finite Markov chain. The proposed algorithm computes the necessary perturbations in the local agents' behavior, which guarantees convergence to the desired observed state of the swarm. The ergodicity property of the swarm, which is induced as a result of the irreducibility of the agent models, implies that while the local behavior of the agents converges to the desired behavior only in the time average, the overall swarm behavior converges to the specification and stays there at all times. A simulation example illustrates the underlying concept.
UR - http://www.scopus.com/inward/record.url?scp=70349615413&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349615413&partnerID=8YFLogxK
U2 - 10.1109/TSMCB.2009.2020173
DO - 10.1109/TSMCB.2009.2020173
M3 - Article
C2 - 19447731
AN - SCOPUS:70349615413
SN - 1083-4419
VL - 39
SP - 1505
EP - 1515
JO - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IS - 6
ER -