Search

We study the classical problem introduced by R. Isaacs and S. Gal of minimizing the time to find a hidden point H on a network Q moving from a known starting point. Rather than adopting the traditional continuous unit speed path paradigm, we use the dynamic "expanding search" paradigm recently introduced by the authors. Here the regions S(t) that have been searched by time t are increasing from the starting point and have total length t. Roughly speaking the search follows a sequence of arcs ai such that each one starts at some point of an earlier one. This type of search is often carried out by real life search teams in the hunt for missing persons, escaped convicts, terrorists or lost airplanes. The paper which introduced this type of search solved the adversarial problem (where H is hidden to maximize the time to be found) for the cases where Q is a tree or is 2-arc-connected. This paper's main contribution is to give two strategy classes which can be used on any network and have expected search times which are within a factor close to 1 of the value of the game (minimax search time). These strategies classes are respectively optimal for trees and 2-arc-connected networks. We also solve the game for circle-and-spike networks, which can be considered as the simplest class of networks for which a solution was previously unknown. [ABSTRACT FROM AUTHOR]

Search games with capacities are bipersonal zero-sum games where a player has to hide a number of objects or an amount of material in a fixed number of containers and his opponent attempts to locate them. In this article, we deal with games on a discrete structureless set and on a discrete set with linear order. In both cases, the capacities under consideration are continuous. Some of the games studied generalize previously studied games. [ABSTRACT FROM AUTHOR]

In an accumulation game, a hider places objects at locations, and a seeker examines these locations. If the seeker discovers an object, the seeker confiscates it. The goal of the hider is to accumulate a certain number of objects before a given time, and the goal of the seeker is to prevent this. In this paper, we first classify various possible variations on the accumulation game. Next, we discuss the so-called noisy accumulation game in which the hider can observe each action of the seeker. We present the solution of this game for all but some marginal cases and illustrate it with computational examples. [ABSTRACT FROM AUTHOR]