Results 1  10
of
89
Constraint Networks
, 1992
"... Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expression ..."
Abstract

Cited by 1149 (43 self)
 Add to MetaCart
Constraintbased reasoning is a paradigm for formulating knowledge as a set of constraints without specifying the method by which these constraints are to be satisfied. A variety of techniques have been developed for finding partial or complete solutions for different kinds of constraint expressions. These have been successfully applied to diverse tasks such as design, diagnosis, truth maintenance, scheduling, spatiotemporal reasoning, logic programming and user interface. Constraint networks are graphical representations used to guide strategies for solving constraint satisfaction problems (CSPs).
Property Testing in Bounded Degree Graphs
 Algorithmica
, 1997
"... We further develop the study of testing graph properties as initiated by Goldreich, Goldwasser and Ron. Whereas they view graphs as represented by their adjacency matrix and measure distance between graphs as a fraction of all possible vertex pairs, we view graphs as represented by boundedlength in ..."
Abstract

Cited by 133 (38 self)
 Add to MetaCart
We further develop the study of testing graph properties as initiated by Goldreich, Goldwasser and Ron. Whereas they view graphs as represented by their adjacency matrix and measure distance between graphs as a fraction of all possible vertex pairs, we view graphs as represented by boundedlength incidence lists and measure distance between graphs as a fraction of the maximum possible number of edges. Thus, while the previous model is most appropriate for the study of dense graphs, our model is most appropriate for the study of boundeddegree graphs. In particular, we present randomized algorithms for testing whether an unknown boundeddegree graph is connected, kconnected (for k ? 1), planar, etc. Our algorithms work in time polynomial in 1=ffl, always accept the graph when it has the tested property, and reject with high probability if the graph is fflaway from having the property. For example, the 2Connectivity algorithm rejects (w.h.p.) any Nvertex ddegree graph for which more ...
Shortestpath and minimumdelay algorithms in networks with timedependent edgelength
 Journal of the ACM
, 1990
"... We consider in this paper the shortestpath problem in networks in which the delay (or weight) of the edges changes with time according to arbitrary functions. We present algorithms for finding the shortestpath and minimumdelay under various waiting constraints and investigate the properties of th ..."
Abstract

Cited by 128 (6 self)
 Add to MetaCart
(Show Context)
We consider in this paper the shortestpath problem in networks in which the delay (or weight) of the edges changes with time according to arbitrary functions. We present algorithms for finding the shortestpath and minimumdelay under various waiting constraints and investigate the properties of the derived path. We show that if departure time from the source node is unrestricted then a shortest path can be found that is simple and achieves a delay as short as the most unrestricted path. In the case of restricted transit, it is shown that there exist cases where the minimum delay is finite but the path that achieves it is infinite.
Testing Monotonicity
, 1999
"... We present a (randomized) test for monotonicity of Boolean functions. Namely, given the ability to query an unknown function f : f0; 1g 7! f0; 1g at arguments of its choice, the test always accepts a monotone f , and rejects f with high probability if it is fflfar from being monotone (i.e., e ..."
Abstract

Cited by 78 (15 self)
 Add to MetaCart
We present a (randomized) test for monotonicity of Boolean functions. Namely, given the ability to query an unknown function f : f0; 1g 7! f0; 1g at arguments of its choice, the test always accepts a monotone f , and rejects f with high probability if it is fflfar from being monotone (i.e., every monotone function differs from f on more than an ffl fraction of the domain).
The MultiTree Approach to Reliability in Distributed Networks
 Information and Computation
, 1984
"... Consider a network of asynchronous processors communicating by sending messages over unreliable lines. There are many advantages to restricting all communications to a spanning tree. To overcome the possible failure of k <k edges, we describe a communication protocol which uses k rooted spanning ..."
Abstract

Cited by 76 (1 self)
 Add to MetaCart
(Show Context)
Consider a network of asynchronous processors communicating by sending messages over unreliable lines. There are many advantages to restricting all communications to a spanning tree. To overcome the possible failure of k <k edges, we describe a communication protocol which uses k rooted spanning trees having the property that for every vertex v the paths from v to the root are edgedisjoint. An algorithm to find two such trees in a 2 edgeconnected graph is described that runs in time proportional to the number of edges in the graph. This algorithm has a distributed version which finds the two trees even when a single edge fails during their construction. The two trees them may be used to transform certain centralized algorithms to distributed, reliable and efficient ones.  1  1. INTRODUCTION Consider a network G=(V ,E ) of n = V asynchronous processors (or vertices) connected by e = E edges. The network may be used to conduct a computation which cannot be done in a single pr...
Improved Time Bounds for the Maximum Flow Problem
, 1987
"... A Recently, Goldberg proposed a new approach to the maximum network flow problem. The approach yields a very simple algorithm running in O(n) "time on nvertex networks. Incorporation of the dynamic tree data structure of Sleator and Tarjan yields a more complicated algorithm with a running ti ..."
Abstract

Cited by 48 (11 self)
 Add to MetaCart
A Recently, Goldberg proposed a new approach to the maximum network flow problem. The approach yields a very simple algorithm running in O(n) "time on nvertex networks. Incorporation of the dynamic tree data structure of Sleator and Tarjan yields a more complicated algorithm with a running time of O(nm log (n2/m)) on medge netvorks.'Ahuja and Orlin developedIa variant of GoldbeWrs algorithm, that uses scaling and runs in O(nm + h2 logU) time on networks with integer edge capacities bounded by U. * this paper w. t obtaina modification of the AhujaOrlin algorithm with a running time of 0(nm + n2 loU). We4heshow thatthe use of dynamic trees in this algologlogUrithm further reduces the time bound to 0(nm log ( n logU + 2)). This result m loglogU demonstrates that the combined use of scaling and dynamic trees results in speed
Pathbased depthfirst search for strong and biconnected components
 Information Processing Letters
, 2000
"... Key words: Graph, depthfirst search, strongly connected component, biconnected component, stack. ..."
Abstract

Cited by 38 (0 self)
 Add to MetaCart
(Show Context)
Key words: Graph, depthfirst search, strongly connected component, biconnected component, stack.
Local Ratio: A Unified Framework for Approximation Algorithms
 ACM Computing Surveys
, 2004
"... ..."
Lower Bounds for Fully Dynamic Connectivity Problems in Graphs
, 1998
"... We prove lower bounds on the complexity of maintaining fully dynamic kedge or kvertex connectivity in plane graphs and in (k − 1)vertex connected graphs. We show an amortized lower bound of �(log n/k(log log n + log b)) per edge insertion, deletion, or query operation in the cell probe model, whe ..."
Abstract

Cited by 36 (5 self)
 Add to MetaCart
We prove lower bounds on the complexity of maintaining fully dynamic kedge or kvertex connectivity in plane graphs and in (k − 1)vertex connected graphs. We show an amortized lower bound of �(log n/k(log log n + log b)) per edge insertion, deletion, or query operation in the cell probe model, where b is the word size of the machine and n is the number of vertices in G. We also show an amortized lower bound of �(log n/(log log n + log b)) per operation for fully dynamic planarity testing in embedded graphs. These are the first lower bounds for fully dynamic connectivity problems.
On the spacetime tradeoff in solving constraint satisfaction problems
 in: Fourteenth International Joint Conference on Artificial Intelligence (IJCAI
, 1995
"... A common technique for bounding the runtime required to solve a constraint satisfaction problem is to exploit the structure of the problem's constraint graph [Dechter, 92]. We show that a simple structurebased technique with a minimal space requirement, pseudotree search [Freuder & Quinn, ..."
Abstract

Cited by 36 (2 self)
 Add to MetaCart
A common technique for bounding the runtime required to solve a constraint satisfaction problem is to exploit the structure of the problem's constraint graph [Dechter, 92]. We show that a simple structurebased technique with a minimal space requirement, pseudotree search [Freuder & Quinn, 85], is capable of bounding runtime almost as effectively as the best exponential spaceconsuming schemes. Specifically, if we let n denote the number of variables in the problem, w * denote the exponent in the complexity function of the best structurebased techniques, and h denote the exponent from pseudotree search, we show h < {w * + 1) (lg(n) + 1). The result should allow reductions in the amount of realtime accessible memory required for predicting runtime when solving CSP equivalent problems. 1