3,387 research outputs found
Parameterized Analysis of the Cops and Robber Game
Pursuit-evasion games have been intensively studied for several decades due to their numerous applications in artificial intelligence, robot motion planning, database theory, distributed computing, and algorithmic theory. Cops and Robber (CnR) is one of the most well-known pursuit-evasion games played on graphs, where multiple cops pursue a single robber. The aim is to compute the cop number of a graph, k, which is the minimum number of cops that ensures the capture of the robber.
From the viewpoint of parameterized complexity, CnR is W[2]-hard parameterized by k [Fomin et al., TCS, 2010]. Thus, we study structural parameters of the input graph. We begin with the vertex cover number (vcn). First, we establish that k ? vcn/3+1. Second, we prove that CnR parameterized by vcn is FPT by designing an exponential kernel. We complement this result by showing that it is unlikely for CnR parameterized by vcn to admit a polynomial compression. We extend our exponential kernels to the parameters cluster vertex deletion number and deletion to stars number, and design a linear vertex kernel for neighborhood diversity. Additionally, we extend all of our results to several well-studied variations of CnR
Path Planning Problems with Side Observations-When Colonels Play Hide-and-Seek
Resource allocation games such as the famous Colonel Blotto (CB) and
Hide-and-Seek (HS) games are often used to model a large variety of practical
problems, but only in their one-shot versions. Indeed, due to their extremely
large strategy space, it remains an open question how one can efficiently learn
in these games. In this work, we show that the online CB and HS games can be
cast as path planning problems with side-observations (SOPPP): at each stage, a
learner chooses a path on a directed acyclic graph and suffers the sum of
losses that are adversarially assigned to the corresponding edges; and she then
receives semi-bandit feedback with side-observations (i.e., she observes the
losses on the chosen edges plus some others). We propose a novel algorithm,
EXP3-OE, the first-of-its-kind with guaranteed efficient running time for SOPPP
without requiring any auxiliary oracle. We provide an expected-regret bound of
EXP3-OE in SOPPP matching the order of the best benchmark in the literature.
Moreover, we introduce additional assumptions on the observability model under
which we can further improve the regret bounds of EXP3-OE. We illustrate the
benefit of using EXP3-OE in SOPPP by applying it to the online CB and HS games.Comment: Previously, this work appeared as arXiv:1911.09023 which was
mistakenly submitted as a new article (has been submitted to be withdrawn).
This is a preprint of the work published in Proceedings of the 34th AAAI
Conference on Artificial Intelligence (AAAI
Visibility Graphs, Dismantlability, and the Cops and Robbers Game
We study versions of cop and robber pursuit-evasion games on the visibility
graphs of polygons, and inside polygons with straight and curved sides. Each
player has full information about the other player's location, players take
turns, and the robber is captured when the cop arrives at the same point as the
robber. In visibility graphs we show the cop can always win because visibility
graphs are dismantlable, which is interesting as one of the few results
relating visibility graphs to other known graph classes. We extend this to show
that the cop wins games in which players move along straight line segments
inside any polygon and, more generally, inside any simply connected planar
region with a reasonable boundary. Essentially, our problem is a type of
pursuit-evasion using the link metric rather than the Euclidean metric, and our
result provides an interesting class of infinite cop-win graphs.Comment: 23 page
Characterizations and algorithms for generalized Cops and Robbers games
We propose a definition of generalized Cops and Robbers games where there are
two players, the Pursuer and the Evader, who each move via prescribed rules. If
the Pursuer can ensure that the game enters into a fixed set of final
positions, then the Pursuer wins; otherwise, the Evader wins. A relational
characterization of the games where the Pursuer wins is provided. A precise
formula is given for the length of the game, along with an algorithm for
computing if the Pursuer has a winning strategy whose complexity is a function
of the parameters of the game. For games where the position of one player does
not affect the available moves of he other, a vertex elimination ordering
characterization, analogous to a cop-win ordering, is given for when the
Pursuer has a winning strategy
Cops vs. Gambler
We consider a variation of cop vs.\ robber on graph in which the robber is
not restricted by the graph edges; instead, he picks a time-independent
probability distribution on and moves according to this fixed
distribution. The cop moves from vertex to adjacent vertex with the goal of
minimizing expected capture time. Players move simultaneously. We show that
when the gambler's distribution is known, the expected capture time (with best
play) on any connected -vertex graph is exactly . We also give bounds on
the (generally greater) expected capture time when the gambler's distribution
is unknown to the cop.Comment: 6 pages, 0 figure
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