We study the problem of searching for a hidden target in an environment that is modeled by an edge-weighted graph. A sequence of edges is chosen starting from a given root vertex such that each edge is adjacent to a previously chosen edge. This search paradigm, known as expanding search was recently introduced by Apern and Lidbetter [2013] for modeling problems such as searching for coal or minesweeping in which the cost of re-exploration is negligible. It can also be used to model a team of searchers successively splitting up in the search for a hidden adversary or explosive device, for example. We define the search ratio of an expanding search as the maximum over all vertices of the ratio of the time taken to reach the vertex and the shortest-path cost to it from the root. This can be interpreted as a measure of the multiplicative regret incurred in searching, and similar objectives have previously been studied in the context of conventional (pathwise) search. In this paper we address algorithmic and computational issues of minimizing the search ratio over all expanding searches, for a variety of search environments, including general graphs, trees and star-like graphs. Our main results focus on the problem of finding the randomized expanding search with minimum expected search ratio, which is equivalent to solving a zero-sum game between a Searcher and a Hider. We solve these problems for certain classes of graphs, and obtain constant-factor approximations for others.
We consider a search game for an immobile hider on one arc of the union of n graphs joined at one or two points. We evaluate a lower bound on the value of a strategy for the hider on this union. When we have identical graphs, we give the conditions under which the value of the strategy for the hider on this union is greater than or equal to n times the value of this strategy on one graph. We also solve search games on graphs, consisting of an odd number of arcs, each of length one, joining two points. The authors analyze two-person zero-sum search games of the following type. Play takes place on a network; the hider must choose a node and remain there while the searcher can choose the node at which he starts. To detect the hider, the searcher needs to conduct a search at the node chosen by the hider. Searching a node involves a cost which can vary from node to node. In addition to the search costs, the searcher also incurs travelling costs represented by distances on the edges. The costs are known to both players and the searcher wants to minimize his total costs. An upper bound for the value of the game is obtained and a lower bound when the network has all its edge lengths the same. Restricting attention to networks which have all their edges of the same length, the upper, and lower bounds are shown to coincide for some networks including Hamiltonian ones. Some results for the star and line networks are also given. © 2013 Wiley Periodicals, Inc. NETWORKS, 2013 We analyze a zero-sum game between a blind unit-speed searcher and a stationary hider on a given network Q, where the payoff is the time for the searcher to reach the hider. In contrast to the standard game studied in the literature, we do not assume that the searcher has to start from a fixed point (known to the hider) but can choose his starting point. We show that for some networks, including trees, the optimal searcher, and hider strategies have a simple structure. © 2008 Wiley Periodicals, Inc. NETWORKS, 2008 Consider a search game with an immobile hider in a graph. A Chinese postman tour is a closed trajectory which visits all the points of the graph and has minimal length. We show that encircling the Chinese postman tour in a random direction is an optimal search strategy if and only if the graph is weakly Eulerian (i.e it consists of several Eulerian curves connected in a tree-like structure). The authors analyse two-person zero-sum search games in which play takes place on a network and in discrete time. The hider first chooses a node and remains there for the duration of the game. The searcher then chooses a node and searches there. At each subsequent time instant the searcher moves from the node he occupies to an adjacent node and decides whether or not to search it. Play terminates when the searcher is at the node chosen by the hider and searches there. The searcher incurs costs in moving from one node to another and also when a node is searched. The searcher wants to minimize the costs of finding the hider and the hider wants to maximize them. The paper has two main strands. The first investigates these games on directed, not necessarily strongly connected, networks; previous work has tended to concentrate on undirected networks. The second complements previous work on undirected networks by obtaining results for the case when the search cost is the same for all nodes. We consider search games in which the searcher moves along a continuous trajectory in a set Q until he captures the hider, where Q is either a network or a two (or more) dimensional region. We distinguish between two types of games; in the first type which is considered in the first part of the paper, the hider is immobile while in the second type of games which is considered in the rest of the paper, the hider is mobile. A complete solution is presented for some of the games, while for others only upper and lower bounds are given and some open problems associated with those games are presented for further research. In the (zero-sum) search game Γ(G, x) proposed by Isaacs, the Hider picks a point H in the network G and the Searcher picks a unit speed path S(t) in G with S(0) = x. The payoff to the maximizing Hider is the time T = T(S, H) = min t : S(t) = H required for the Searcher to find the Hider. An extensive theory of such games has been developed in the literature. This paper considers the related games Γ(G), where the requirement S(0) = x is dropped, and the Searcher is allowed to choose his starting point. This game has been solved by Dagan and Gal for the important case where G is a tree, and by Alpern for trees with Eulerian networks attached. Here, we extend those results to a wider class of networks, employing theory initiated by Reijnierse and Potters and completed by Gal, for the fixed-start games Γ(G, x). Our results may be more easily interpreted as determining the best worst-case method of searching a network from an arbitrary starting point. In this paper we discuss a type of search game with immobile hider on a graph. If the graph is weakly cyclic (i.e. no edge lies on two different cycles) we determine the value of the game and give an easy way to compute optimal strategies for the players. The value is half the length of a quasi-Euler path, i.e. a closed path of minimal length that visits all points of the network.