Maximizing the expected number of components in an online search of a graph
Résumé
The following optimal stopping problem is considered. The vertices of a graph $G$ are revealed one by one, in a random order, to a selector. He aims to stop this process at a time $t$ that maximizes the expected number of connected components in the graph $G˜t$, induced by the currently revealed vertices. The selector knows $G$ in advance, but different versions of the game are considered depending on the information that he gets about $G˜t$. We show that when $G$ has $N$ vertices and maximum degree of order $o(√ N)$, then the number of components of $G˜t$ is concentrated around its mean, which implies that playing the optimal strategy the selector does not benefit much by receiving more information about $G˜t$. Results of similar nature were previously obtained by M. Laso« for the case where $G$ is a $k$-tree (for constant $k$). We also consider the particular cases where $G$ is a square, triangular or hexagonal lattice, showing that an optimal selector gains $cN$ components and we compute $c$ with an error less than 0.005 in each case.
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