Genericity in Topological Dynamics

We study genericity of dynamical properties in the space of homeomorphisms of the Cantor set and in the space of subshifts of a suitably large shift space. These rather different settings are related by a Glasner-King type correspondence: genericity in one is equivalent to genericity in the other. By applying symbolic techniques in the shift-space model we derive new results about genericity of dynamical properties for transitive and totally transitive homeomorphisms of the Cantor set. We show that the isomorphism class of the universal odometer is generic in the space of transitive systems. On the other hand, the space of totally transitive systems displays much more varied dynamics. In particular, we show that in this space the isomorphism class of every Cantor system without periodic points is dense, and the following properties are generic: minimality, zero entropy, disjointness from a fixed totally transitive system, weak mixing, strong mixing, and minimal self joinings. The last two stand in striking contrast to the situation in the measure-preserving category. We also prove a correspondence between genericity of dynamical properties in the measure-preserving category and genericity of systems supporting an invariant measure with the same property.Comment: 48 pages, to appear in Ergodic Theory Dynamical Systems. v2: revised exposition, added proof that the universal odometer is generic among transitive Cantor homeomorphism

Approximate solutions for expanding search games on general networks

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

Searching a variable speed network

A point lies on a network according to some unknown probability distribution. Starting at a specified root of the network, a Searcher moves to find this point at speeds that depend on his location and direction. He seeks the randomized search algorithm that minimizes the expected search time. This is equivalent to modeling the problem as a zero-sum hide-and-seek game whose value is called the search value of the network. We make a new and direct derivation of an explicit formula for the search value of a tree, proving that it is equal to half the sum of the minimum tour time of the tree and a quantity called its incline. The incline of a tree is an average over the leaf nodes of the difference between the time taken to travel from the root to a leaf node and the time taken to travel from a leaf node to the root. This difference can be interpreted as height of a leaf node, assuming uphill is slower than downhill. We then apply this formula to obtain numerous results for general networks. We also introduce a new general method of comparing the search value of networks that differ in a single arc. Some simple networks have very complicated optimal strategies that require mixing of a continuum of pure strategies. Many of our results generalize analogous ones obtained for constant velocity (in both directions) by S. Gal, but not all of those results can be extended

Search for an immobile Hider in a known subset of a network

A unit speed Searcher, constrained to start in a given closed set S, wishes to quickly find a point x known to be located in a given closed subset H of a metric network Q. This defines a game G=G(Q,H,S), where the payoff to the maximizing Hider is the time for the Searcher path to reach x. Lengths on Q are defined by a measure λ, which then defines distance as least length of connecting path. For trees Q, we find that the minimax search time (value V of G) is given by V=λ(H)-d_{H}(S)/2, where d_{H}(S) is what we call the `H-diameter of S', and equals the usual diameter d(S) of S in the case H=Q. For the classical case of Gal where the S is a singleton and H=Q, our formula reduces to his result V=λ(Q). If S=H=Q, our formula gives Dagan and Gal's result V=λ(Q)-d(Q)/2. In all other cases, our result is new. Optimal searches consist of minimum length paths covering H which start and end at points of S, traversed equiprobably in either direction

The importance of voting order for decisions by sequential majority voting

A jury of experts is often convened to decide between two states of Nature relevant to a managerial decision. For example, a legal jury decides between "innocent" and "guilty", while an economic jury decides between "high" and "low" growth when there is an investment decision. Usually the jurors vary in their abilities to determine the actual state. When the jurors make their collective decision by sequential majority voting, the order of voting in terms of juror ability can affect the optimal probability Q of reaching a correct verdict. We show that when the jury has size three, Q is maximized if the juror of median ability votes first. When voting in this order, sequential voting can close more than 50% of the gap (in terms of Q) between simultaneous voting and the verdict that would be reached without voting if the jurors' private information were made public. Our results have implications for larger juries, where we answer an age-old question by showing that voting by seniority (decreasing ability order) is significantly better than by anti-seniority (increasing ability order). To obtain our new results we introduce a richer notion of private information. Instead of the binary information assumed since Condorcet (for "innocent" or "guilty"), we give each juror a number in interval [-1,+1] with larger values indicating stronger signals for "innocent"

Optimal trade-off between speed and acuity when searching for a small object

A Searcher seeks to find a stationary Hider located at some point H (not necessarily a node) on a given network Q. The Searcher can move along the network from a given starting point at unit speed, but to actually find the Hider she must pass it while moving at a fixed slower speed (which may depend on the arc). In this “bimodal search game,” the payoff is the first time the Searcher passes the Hider while moving at her slow speed. This game models the search for a small or well hidden object (e.g., a contact lens, improvised explosive device, predator search for camouflaged prey). We define a bimodal Chinese postman tour as a tour of minimum time δ which traverses every point of every arc at least once in the slow mode. For trees and weakly Eulerian networks (networks containing a number of disjoint Eulerian cycles connected in a tree-like fashion) the value of the bimodal search game is δ/2. For trees, the optimal Hider strategy has full support on the network. This differs from traditional search games, where it is optimal for him to hide only at leaf nodes. We then consider the notion of a lucky Searcher who can also detect the Hider with a positive probability q even when passing him at her fast speed. This paper has particular importance for demining problems

Hide-and-seek games on a network, using combinatorial search paths

This paper introduces a new search paradigm to hide-and-seek games on networks. The Hider locates at any point on any arc. The Searcher adopts a “combinatorial” path when searching the network: a sequence of arcs, each adjacent to the last, and traced out at unit speed. In previous literature the Searcher was allowed “simple motion,” any unit speed path, including ones that turn around inside an arc. The new approach more closely models real problems such as search for improvised explosive devices using vehicles that can only turn around at particular locations on a road. The search game is zero sum, with the time taken to find the Hider as the payoff. Using a lemma giving an upper bound for the expected search time on a semi Eulerian network, we solve the search game on a network Q3 consisting of two nodes connected by three arcs of arbitrary lengths. When two Q3 networks with unit length arcs are linked by two small central arcs incident at the start node, one of these arcs must be traversed at least three times in an optimal search. This property holds for both combinatorial paths and simple motion paths, and the latter makes it a counterexample to a conjecture of Gal, which said that two traversals were always sufficient