  The linear search problem, informally known as the cow path problem, is one
of the fundamental problems in search theory. In this problem, an immobile
target is hidden at some unknown position on an unbounded line, and a mobile
searcher, initially positioned at some specific point of the line called the
root, must traverse the line so as to locate the target. The objective is to
minimize the worst-case ratio of the distance traversed by the searcher to the
distance of the target from the root, which is known as the competitive ratio
of the search.
  In this work we study this problem in a setting in which the searcher has a
hint concerning the target. We consider three settings in regards to the nature
of the hint: i) the hint suggests the exact position of the target on the line;
ii) the hint suggests the direction of the optimal search (i.e., to the left or
the right of the root); and iii) the hint is a general k-bit string that
encodes some information concerning the target. Our objective is to study the
Pareto-efficiency of strategies in this model. Namely, we seek optimal, or
near-optimal tradeoffs between the searcher's performance if the hint is
correct (i.e., provided by a trusted source) and if the hint is incorrect
(i.e., provided by an adversary).
