278 research outputs found
Playing Games in the Baire Space
We solve a generalized version of Church's Synthesis Problem where a play is
given by a sequence of natural numbers rather than a sequence of bits; so a
play is an element of the Baire space rather than of the Cantor space. Two
players Input and Output choose natural numbers in alternation to generate a
play. We present a natural model of automata ("N-memory automata") equipped
with the parity acceptance condition, and we introduce also the corresponding
model of "N-memory transducers". We show that solvability of games specified by
N-memory automata (i.e., existence of a winning strategy for player Output) is
decidable, and that in this case an N-memory transducer can be constructed that
implements a winning strategy for player Output.Comment: In Proceedings Cassting'16/SynCoP'16, arXiv:1608.0017
Pattern Matching for sets of segments
In this paper we present algorithms for a number of problems in geometric
pattern matching where the input consist of a collections of segments in the
plane. Our work consists of two main parts. In the first, we address problems
and measures that relate to collections of orthogonal line segments in the
plane. Such collections arise naturally from problems in mapping buildings and
robot exploration.
We propose a new measure of segment similarity called a \emph{coverage
measure}, and present efficient algorithms for maximising this measure between
sets of axis-parallel segments under translations. Our algorithms run in time
O(n^3\polylog n) in the general case, and run in time O(n^2\polylog n) for
the case when all segments are horizontal. In addition, we show that when
restricted to translations that are only vertical, the Hausdorff distance
between two sets of horizontal segments can be computed in time roughly
O(n^{3/2}{\sl polylog}n). These algorithms form significant improvements over
the general algorithm of Chew et al. that takes time . In the
second part of this paper we address the problem of matching polygonal chains.
We study the well known \Frd, and present the first algorithm for computing the
\Frd under general translations. Our methods also yield algorithms for
computing a generalization of the \Fr distance, and we also present a simple
approximation algorithm for the \Frd that runs in time O(n^2\polylog n).Comment: To appear in the 12 ACM Symposium on Discrete Algorithms, Jan 200
Deterministic Fully Dynamic SSSP and More
We present the first non-trivial fully dynamic algorithm maintaining exact
single-source distances in unweighted graphs. This resolves an open problem
stated by Sankowski [COCOON 2005] and van den Brand and Nanongkai [FOCS 2019].
Previous fully dynamic single-source distances data structures were all
approximate, but so far, non-trivial dynamic algorithms for the exact setting
could only be ruled out for polynomially weighted graphs (Abboud and
Vassilevska Williams, [FOCS 2014]). The exact unweighted case remained the main
case for which neither a subquadratic dynamic algorithm nor a quadratic lower
bound was known.
Our dynamic algorithm works on directed graphs, is deterministic, and can
report a single-source shortest paths tree in subquadratic time as well. Thus
we also obtain the first deterministic fully dynamic data structure for
reachability (transitive closure) with subquadratic update and query time. This
answers an open problem of van den Brand, Nanongkai, and Saranurak [FOCS 2019].
Finally, using the same framework we obtain the first fully dynamic data
structure maintaining all-pairs -approximate distances within
non-trivial sub- worst-case update time while supporting optimal-time
approximate shortest path reporting at the same time. This data structure is
also deterministic and therefore implies the first known non-trivial
deterministic worst-case bound for recomputing the transitive closure of a
digraph.Comment: Extended abstract to appear in FOCS 202
Reachability in Vector Addition Systems is Primitive-Recursive in Fixed Dimension
The reachability problem in vector addition systems is a central question,
not only for the static verification of these systems, but also for many
inter-reducible decision problems occurring in various fields. The currently
best known upper bound on this problem is not primitive-recursive, even when
considering systems of fixed dimension. We provide significant refinements to
the classical decomposition algorithm of Mayr, Kosaraju, and Lambert and to its
termination proof, which yield an ACKERMANN upper bound in the general case,
and primitive-recursive upper bounds in fixed dimension. While this does not
match the currently best known TOWER lower bound for reachability, it is
optimal for related problems
Fast Deterministic Fully Dynamic Distance Approximation
In this paper, we develop deterministic fully dynamic algorithms for
computing approximate distances in a graph with worst-case update time
guarantees. In particular, we obtain improved dynamic algorithms that, given an
unweighted and undirected graph undergoing edge insertions and
deletions, and a parameter , maintain
-approximations of the -distance between a given pair of
nodes and , the distances from a single source to all nodes
("SSSP"), the distances from multiple sources to all nodes ("MSSP"), or the
distances between all nodes ("APSP").
Our main result is a deterministic algorithm for maintaining
-approximate -distance with worst-case update time
(for the current best known bound on the matrix multiplication
exponent ). This even improves upon the fastest known randomized
algorithm for this problem. Similar to several other well-studied dynamic
problems whose state-of-the-art worst-case update time is , this
matches a conditional lower bound [BNS, FOCS 2019]. We further give a
deterministic algorithm for maintaining -approximate
single-source distances with worst-case update time , which also
matches a conditional lower bound.
At the core, our approach is to combine algebraic distance maintenance data
structures with near-additive emulator constructions. This also leads to novel
dynamic algorithms for maintaining -emulators that improve
upon the state of the art, which might be of independent interest. Our
techniques also lead to improved randomized algorithms for several problems
such as exact -distances and diameter approximation.Comment: Changes to the previous version: improved bounds for approximate st
distances using new algebraic data structure
Planar Reachability Under Single Vertex or Edge Failures
International audienceIn this paper we present an efficient reachability oracle under single-edge or single-vertex failures for planar directed graphs. Specifically, we show that a planar digraph G can be preprocessed in O(n log 2 n/log log n) time, producing an O(n log n)-space data structure that can answer in O(log n) time whether u can reach v in G if the vertex x (the edge f) is removed from G, for any query vertices u, v and failed vertex x (failed edge f). To the best of our knowledge, this is the first data structure for planar directed graphs with nearly optimal preprocessing time that answers all-pairs queries under any kind of failures in polylogarithmic time. We also consider 2-reachability problems, where we are given a planar digraph G and we wish to determine if there are two vertex-disjoint (edge-disjoint) paths from u to v, for query vertices u, v. In this setting we provide a nearly optimal 2-reachability oracle, which is the existential variant of the reachability oracle under single failures, with the following bounds. We can construct in O(n polylog n) time an O(n log 3+o(1) n)-space data structure that can check in O(log 2+o(1) n) time for any query vertices u, v whether v is 2-reachable from u, or otherwise find some separating vertex (edge) x lying on all paths from u to v in G. To obtain our results, we follow the general recursive approach of Thorup for reachability in planar graphs [J. ACM '04] and we present new data structures which generalize dominator trees and previous data structures for strong-connectivity under failures [Georgiadis et al., SODA '17]. Our new data structures work also for general digraphs and may be of independent interest
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