Results 1 - 10
of
29,164
Estimating Search Tree Size
- In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI ’06
, 2006
"... We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronologi-cal backtracking. The second is a recursive method based on assuming that the unexplored part of the search tree will be simil ..."
Abstract
-
Cited by 26 (2 self)
- Add to MetaCart
We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronologi-cal backtracking. The second is a recursive method based on assuming that the unexplored part of the search tree
Abstract Estimating Search Tree Size
"... We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronological backtracking. The second is a recursive method based on assuming that the unexplored part of the search tree will be simila ..."
Abstract
- Add to MetaCart
We propose two new online methods for estimating the size of a backtracking search tree. The first method is based on a weighted sample of the branches visited by chronological backtracking. The second is a recursive method based on assuming that the unexplored part of the search tree
On guaranteeing polynomially bounded search tree size
- In CP
, 2011
"... Abstract. Much work has been done on describing tractable classes of constraint networks. Most of the known tractable examples are described by either restricting the structure of the networks, or their language. In-deed, for both structural or language restrictions very strong dichotomy results hav ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
Abstract. Much work has been done on describing tractable classes of constraint networks. Most of the known tractable examples are described by either restricting the structure of the networks, or their language. In-deed, for both structural or language restrictions very strong dichotomy results have been proven and in both cases it is likely that all practical examples have already been discovered. As such it is timely to consider tractability which cannot be described by language or structural restrictions. This is the focus of the work here. In this paper we investigate a novel reason for tractability: having at least one variable ordering for which the number of partial solutions to the first n variables is bounded by a polynomial in n. We show that the presence of sufficient functional constraints can guar-antee this property and we investigate the complexity of finding good variable orderings based on different notions of functionality. What is more we identify a completely novel reason for tractability based on so called Turan sets.
Estimating Search Tree Size with Duplicate Detection
"... In this paper we introduce Stratified Sampling with Du-plicate Detection (SSDD), an algorithm for estimating the number of state expansions performed by heuris-tic search algorithms seeking solutions in state spaces represented by undirected graphs. SSDD is general and can be applied to estimate oth ..."
Abstract
- Add to MetaCart
In this paper we introduce Stratified Sampling with Du-plicate Detection (SSDD), an algorithm for estimating the number of state expansions performed by heuris-tic search algorithms seeking solutions in state spaces represented by undirected graphs. SSDD is general and can be applied to estimate
R-trees: A Dynamic Index Structure for Spatial Searching
- INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
, 1984
"... In order to handle spatial data efficiently, as required in computer aided design and geo-data applications, a database system needs an index mechanism that will help it retrieve data items quickly according to their spatial locations However, traditional indexing methods are not well suited to data ..."
Abstract
-
Cited by 2750 (0 self)
- Add to MetaCart
to data objects of non-zero size located m multi-dimensional spaces In this paper we describe a dynamic index structure called an R-tree which meets this need, and give algorithms for searching and updating it. We present the results of a series of tests which indicate that the structure performs well
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NP-complete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
Abstract
-
Cited by 582 (53 self)
- Add to MetaCart
presents a more sophisticated search algorithm for optimal (and anytime) winner determination, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases. We also uncover
Suffix arrays: A new method for on-line string searches
, 1991
"... A new and conceptually simple data structure, called a suffix array, for on-line string searches is intro-duced in this paper. Constructing and querying suffix arrays is reduced to a sort and search paradigm that employs novel algorithms. The main advantage of suffix arrays over suffix trees is that ..."
Abstract
-
Cited by 835 (0 self)
- Add to MetaCart
A new and conceptually simple data structure, called a suffix array, for on-line string searches is intro-duced in this paper. Constructing and querying suffix arrays is reduced to a sort and search paradigm that employs novel algorithms. The main advantage of suffix arrays over suffix trees
Depth-first Iterative-Deepening: An Optimal Admissible Tree Search
- Artificial Intelligence
, 1985
"... The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw-deepening a ..."
Abstract
-
Cited by 527 (24 self)
- Add to MetaCart
The complexities of various search algorithms are considered in terms of time, space, and cost of solution path. It is known that breadth-first search requires too much space and depth-first search can use too much time and doesn't always find a cheapest path. A depth-first iteratiw
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
, 1997
"... A new access meth d, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion o ..."
Abstract
-
Cited by 663 (38 self)
- Add to MetaCart
A new access meth d, called M-tree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion
Fast texture synthesis using tree-structured vector quantization
, 2000
"... Figure 1: Our texture generation process takes an example texture patch (left) and a random noise (middle) as input, and modifies this random noise to make it look like the given example texture. The synthesized texture (right) can be of arbitrary size, and is perceived as very similar to the given ..."
Abstract
-
Cited by 561 (12 self)
- Add to MetaCart
Field texture models and generates textures through a deterministic searching process. We accelerate this synthesis process using tree-structured vector quantization.
Results 1 - 10
of
29,164