Optimal Art Gallery Localization is NP-hard
نویسندگان
چکیده
منابع مشابه
Optimal Art Gallery Localization is NP-hard
Art Gallery Localization (AGL) is the problem of placing a set T of broadcast towers in a simple polygon P in order for a point to locate itself in the interior. For any point p ∈ P : for each tower t ∈ T ∩ V (p) (where V (p) denotes the visibility polygon of p) the point p receives the coordinates of t and the Euclidean distance between t and p. From this information p can determine its coordi...
متن کاملArt Gallery Localization
We study the problem of placing a set T of broadcast towers in a simple polygon P in order for any point to locate itself in the interior of P . Let V (p) denote the visibility polygon of a point p, as the set of all points q ∈ P that are visible to p. For any point p ∈ P : for each tower t ∈ T ∩ V (p) the point p receives the coordinates of t and the Euclidean distance between t and p. From th...
متن کاملNatural Wireless Localization is NP-hard
We consider a special class of art gallery problems inspired by wireless localization. Given a polygonal region P, place and orient guards each of which broadcasts a unique key within a fixed angular range. In contrast to the classical art gallery setting, broadcasts are not blocked by the boundary of P. At any point in the plane one must be able to tell whether or not one is located inside P o...
متن کاملOptimal State Amalgamation is NP-Hard
A state amalgamation of a directed graph is a node contraction which is only permitted under certain configurations of incident edges. In symbolic dynamics, state amalgamation and its inverse operation, state splitting, play a fundamental role in the the theory of subshifts of finite type (SFT): any conjugacy between SFTs, given as vertex shifts, can be expressed as a sequence of symbol splitti...
متن کاملOptimal CQ Reformulation is NP-Hard
As a consequence of the Subgoal Theorem and the Projection Lemma, we need only consider projection views that are defined in terms of subgoals. Unfortunately, despite these improvements, we show that the optimization problem is still NP-Hard in the number of subgoals and free variables in the input query. Our proof strategy is as follows. First, we prune the space of potential reformulations by...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Geometry
سال: 2020
ISSN: 0925-7721
DOI: 10.1016/j.comgeo.2020.101607