24,658 research outputs found
An Atypical Survey of Typical-Case Heuristic Algorithms
Heuristic approaches often do so well that they seem to pretty much always
give the right answer. How close can heuristic algorithms get to always giving
the right answer, without inducing seismic complexity-theoretic consequences?
This article first discusses how a series of results by Berman, Buhrman,
Hartmanis, Homer, Longpr\'{e}, Ogiwara, Sch\"{o}ening, and Watanabe, from the
early 1970s through the early 1990s, explicitly or implicitly limited how well
heuristic algorithms can do on NP-hard problems. In particular, many desirable
levels of heuristic success cannot be obtained unless severe, highly unlikely
complexity class collapses occur. Second, we survey work initiated by Goldreich
and Wigderson, who showed how under plausible assumptions deterministic
heuristics for randomized computation can achieve a very high frequency of
correctness. Finally, we consider formal ways in which theory can help explain
the effectiveness of heuristics that solve NP-hard problems in practice.Comment: This article is currently scheduled to appear in the December 2012
issue of SIGACT New
Computational Complexity and Phase Transitions
Phase transitions in combinatorial problems have recently been shown to be
useful in locating "hard" instances of combinatorial problems. The connection
between computational complexity and the existence of phase transitions has
been addressed in Statistical Mechanics and Artificial Intelligence, but not
studied rigorously.
We take a step in this direction by investigating the existence of sharp
thresholds for the class of generalized satisfiability problems defined by
Schaefer. In the case when all constraints are clauses we give a complete
characterization of such problems that have a sharp threshold.
While NP-completeness does not imply (even in this restricted case) the
existence of a sharp threshold, it "almost implies" this, since clausal
generalized satisfiability problems that lack a sharp threshold are either
1. polynomial time solvable, or
2. predicted, with success probability lower bounded by some positive
constant by across all the probability range, by a single, trivial procedure.Comment: A (slightly) revised version of the paper submitted to the 15th IEEE
Conference on Computational Complexit
Sensor networks and distributed CSP: communication, computation and complexity
We introduce SensorDCSP, a naturally distributed benchmark based on a real-world application that arises in the context of networked distributed systems. In order to study the performance of Distributed CSP (DisCSP) algorithms in a truly distributed setting, we use a discrete-event network simulator, which allows us to model the impact of different network traffic conditions on the performance of the algorithms. We consider two complete DisCSP algorithms: asynchronous backtracking (ABT) and asynchronous weak commitment search (AWC), and perform performance comparison for these algorithms on both satisfiable and unsatisfiable instances of SensorDCSP. We found that random delays (due to network traffic or in some cases actively introduced by the agents) combined with a dynamic decentralized restart strategy can improve the performance of DisCSP algorithms. In addition, we introduce GSensorDCSP, a plain-embedded version of SensorDCSP that is closely related to various real-life dynamic tracking systems. We perform both analytical and empirical study of this benchmark domain. In particular, this benchmark allows us to study the attractiveness of solution repairing for solving a sequence of DisCSPs that represent the dynamic tracking of a set of moving objects.This work was supported in part by AFOSR (F49620-01-1-0076, Intelligent Information Systems Institute and MURI F49620-01-1-0361), CICYT (TIC2001-1577-C03-03 and TIC2003-00950), DARPA (F30602-00-2- 0530), an NSF CAREER award (IIS-9734128), and an Alfred P. Sloan Research Fellowship. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the US Government
Domino Tatami Covering is NP-complete
A covering with dominoes of a rectilinear region is called \emph{tatami} if
no four dominoes meet at any point. We describe a reduction from planar 3SAT to
Domino Tatami Covering. As a consequence it is NP-complete to decide whether
there is a perfect matching of a graph that meets every 4-cycle, even if the
graph is restricted to be an induced subgraph of the grid-graph. The gadgets
used in the reduction were discovered with the help of a SAT-solver.Comment: 10 pages, accepted at The International Workshop on Combinatorial
Algorithms (IWOCA) 201
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