Technical note: Find a hidden “treasure”

This paper deals with a two searchers game and it investigates the problem of how the possibility of finding a hidden object simultaneously by players influences their behavior. Namely, we consider the following two‐sided allocation non‐zero‐sum game on an integer interval [1,n]. Two teams (Player 1 and 2) want to find an immobile object (say, a treasure) hidden at one of n points. Each point i ∈ [1,n] is characterized by a detection parameter λ_i (μ_i) for Player 1 (Player 2) such that p_i(1 ? exp(?λ_ix_i)) (p_i(1 ? exp(?μ_iy_i))) is the probability that Player 1 (Player 2) discovers the hidden object with amount of search effort x_i (y_i) applied at point i where p_i ∈ (0,1) is the probability that the object is hidden at point i. Player 1 (Player 2) undertakes the search by allocating the total amount of effort X(Y). The payoff for Player 1 (Player 2) is 1 if he detects the object but his opponent does not. If both players detect the object they can share it proportionally and even can pay some share to an umpire who takes care that the players do not cheat each other, namely Player 1 gets q₁ and Player 2 gets q₂ where q₁ + q₂ ≤ 1. The Nash equilibrium of this game is found and numerical examples are given. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A fast infiltration game on n arcs

Starting from a safe base, an Infiltrator tries to reach a sensitive zone within a given time limit without being detected by a Guard. The Infiltrator can move with speed at most u, while the Guard can only perform a restricted number of searches. A discrete variant of this zero-sum game played on a graph consisting of two vertices joined by n nonintersecting arcs is investigated. Optimal strategies and an explicit expression for its value are obtained. © 1996 John Wiley & Sons, Inc.     

A remark on a helicopter and submarine game

The article considers a two-person zero-sum game in which the movement of the players is constrained to integer points …, −1, 0, 1, … of a line L. Initially the searcher (hider) is at point x = 0 (x = d, d > 0). The searcher and the hider perform simple motion on L with maximum speeds w and u, respectively, where w > u > 0. Each of the players knows the other's initial position but not the other's subsequent positions. The searcher has a bomb which he can drop at any time during his search. Between the dropping of the bomb and the bomb exploding there is a T time lag. If the bomb explodes at point i and the hider is at point i − 1, or i, or i + 1, then the destruction probability is equal to P, or 1, or P, respectively, where 0 < P < 1. d, w, u, and T are integer constants. The searcher can drop the bomb at integer moments of time t = 0, 1, … . The aim of the searcher is to maximize the probability of the destruction of the hider. © 1993 John Wiley & Sons, Inc.     

A remark on the customs and smuggler game

Baston and Bostock formulated a zero-sum game of exhaustion modeling the problem of Customs trying to stop a Smuggler attempting to ship a cargo of perishable contraband across a strait, when Customs has n speedboats for patrolling. Thomas and Nisgav solved this problem for one speedboat. Baston and Bostock investigated it for two speedboats. This article addresses the solution of the three-boat variant of the Customs and Smuggler game. © 1994 John Wiley & Sons, Inc.     

A search game with a protector

A classic problem in Search Theory is one in which a searcher allocates resources to the points of the integer interval [1, n] in an attempt to find an object which has been hidden in them using a known probability function. In this paper we consider a modification of this problem in which there is a protector who can also allocate resources to the points; allocating these resources makes it more difficult for the searcher to find an object. We model the situation as a two‐person non‐zero‐sum game so that we can take into account the fact that using resources can be costly. It is shown that this game has a unique Nash equilibrium when the searcher's probability of finding an object located at point i is of the form (1 − exp (−λ_ix_i)) exp (−μ_iy_i) when the searcher and protector allocate resources x_i and y_i respectively to point i. An algorithm to find this Nash equilibrium is given. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47:85–96, 2000     

On a ruckle problem in discrete games of ambush

The following zero-sum game is considered. Red chooses in integer interval [1, n] two integer intervals consisting of k and m points where k + m < n, and Blue chooses an integer point in [1, n]. The payoff to Red equals 1 if the point chosen by Blue is at least in one of the intervals chosen by Red, and 0 otherwise. This work complements the results obtained by Ruckle, Baston and Bostock, and Lee. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 353–364, 1997