In this paper, we propose a learning automatabased

weighted cluster formation algorithm calledMCFA in

which the mobility parameters of the hosts are assumed to

be random variables with unknown distributions. In the proposed

clustering algorithm, the expected relative mobility of

each host with respect to all its neighbors is estimated by

sampling its mobility parameters in various epochs. MCFA

is a fully distributed algorithm in which each mobile independently

chooses the neighboring host with the minimum

expected relative mobility as its cluster-head.