  In this paper we study a variant of the Malicious Ma\^{i}tre d' problem. This
problem, attributed to computer scientist Rob Pike in Peter Winkler's book
"Mathematical Puzzles: A Connoisseur's Collection", involves seating diners
around a circular table with napkins placed between each pair of adjacent
settings. The goal of the ma\^{i}tre d' is to seat the diners in a way that
maximizes the number of diners who arrive at the table to find the napkins on
both the left and right of their place already taken by their neighbors.
Previous work described a seating algorithm in which the ma\^{i}tre d' expects
to force about 18% of the diners to be napkinless. In this paper, we show that
if the ma\^{i}tre d' learns each diner's preference for the right or left
napkin before they are placed at the table, this expectation jumps to nearly
$1/3$ (and converges to $1/3$ as the table size gets large). Moreover, our
strategy is optimal for every sequence of diners' preferences.
