This paper deals with a two-person zero-sum search game called search
allocation game (SAG) with a searcher and a target as players, taking account of false
contacts. The searcher distributes his searching resource in a search space to detect
the target and the target moves to evade the searcher. The searcher obtains a profit
of target value on detection of target but expends cost for the search. The payoff of
the game is the expected reward defined by obtained target value minus expended
searching cost. The searcher’s strategy is denoted by a distribution plan about where
and when he distributes his searching resource and the target strategy is the selection
of a path to follow from some options. In the search operation, any sensor cannot
get rid of false contacts caused by signal processing noises and real objects similar to
the true target under noisy environment. On their happening, they make the searcher
waste some time for investigation and interrupt the search operation for a while. There
have been few researches dealing with the SAG with the false contacts. In this paper,
we model the game with false contacts by a stochastic process and discuss a general
procedure to derive an equilibrium point through a nonlinear programming method
for a searcher’s best response to the target’s behavior.
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