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RealTime A* Search With Depthk Lookahead
, 2009
"... We consider realtime planning problems in which some states are unsolvable, i.e., have no path to a goal. Such problems are difficult for realtime planning algorithms such as RTA* in which all states must be solvable. We identify a property called ksafeness, in which the consequences of a bad cho ..."
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Cited by 2 (0 self)
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We consider realtime planning problems in which some states are unsolvable, i.e., have no path to a goal. Such problems are difficult for realtime planning algorithms such as RTA* in which all states must be solvable. We identify a property called ksafeness, in which the consequences of a bad
Lookaheadbased Algorithms for Anytime Induction of Decision Trees
 In ICML’04
, 2004
"... The majority of the existing algorithms for learning decision trees are greedya tree is induced topdown, making locally optimal decisions at each node. In most cases, however, the constructed tree is not globally optimal. Furthermore, the greedy algorithms require a fixed amount of time and are no ..."
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Cited by 18 (4 self)
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and are not able to generate a better tree if additional time is available. To overcome this problem, we present two lookaheadbased algorithms for anytime induction of decision trees, thus allowing tradeoff between tree quality and learning time. The first one is depthk lookahead, where a larger time allocation
kDepth Lookahead Task Scheduling in Network of Heterogeneous Processors
, 2002
"... The objective of the task scheduling is to achieve the minimum execution time of all the tasks with their precedence requirements satis ed. Although several task scheduling heuristics for the heterogeneous environment have been presented in the literature, they overlook the various type of network a ..."
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Cited by 1 (0 self)
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and do not perform eciently on such an environment. We present the new scheduling heuristic which is named the 'kDepth Lookahead.' The proposed heuristic takes the network heterogeneity into consideration and our experimental study shows that the proposed heuristic generates a better schedule
On the Implications of Lookahead Search in Game Playing
, 2012
"... Abstract. Lookahead search is perhaps the most natural and widely used game playing strategy. Given the practical importance of the method, the aim of this paper is to provide a theoretical performance examination of lookahead search in a wide variety of applications. To determine a strategy play us ..."
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into the future. That is, we use depth k search trees and call this approach klookahead search. We apply our method in five wellknown settings: AdWord auctions; industrial organization (Cournot’s model); congestion games; validutility games and basicutility games; costsharing network design games. We
A theoretical examination of practical game playing: Lookahead search
 In SAGT, M. Serna, Ed. Lecture Notes in Computer Science Series
, 2012
"... Abstract. Lookahead search is perhaps the most natural and widely used game playing strategy. Given the practical importance of the method, the aim of this paper is to provide a theoretical performance examination of lookahead search in a wide variety of applications. To determine a strategy play us ..."
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Cited by 3 (1 self)
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into the future. That is, we use depth k search trees and call this approach klookahead search. We apply our method in five wellknown settings: industrial organization (Cournot’s model); AdWord auctions; congestion games; validutility games and basicutility games; costsharing network design games. We
Improving LRTA*(k)
, 2007
"... We identify some weak points of the LRTA*(k) algorithm in the propagation of heuristic changes. To solve them, we present a new algorithm, LRTA*LS(k), that is based on the selection and updating of the interior states of a local space around the current state. It keeps the good theoretical propertie ..."
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Cited by 22 (9 self)
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properties of LRTA*(k), while improving substantially its performance. It is related with a lookahead depth greater than 1. We provide experimental evidence of the benefits of the new algorithm on realtime benchmarks with respect to existing approaches.
Proceedings of the Federated Conference on Computer Science and Information Systems pp. 863–870 ISBN 9788360810224 The embedded left LR parser
"... Abstract—A parser called the embedded left LR(k) parser is defined. It is capable of (a) producing the prefix of the left parse of the input string and (b) stopping not on the endoffile marker but on any string from the set of lookahead strings fixed at the parser generation time. It is aimed at a ..."
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Abstract—A parser called the embedded left LR(k) parser is defined. It is capable of (a) producing the prefix of the left parse of the input string and (b) stopping not on the endoffile marker but on any string from the set of lookahead strings fixed at the parser generation time. It is aimed
Packrat Parsing: a Practical LinearTime Algorithm with Backtracking
, 2002
"... Packrat parsing is a novel and practical method for implementing lineartime parsers for grammars defined in TopDown Parsing Language (TDPL). While TDPL was originally created as a formal model for topdown parsers with backtracking capability, this thesis extends TDPL into a powerful generalpurpo ..."
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Cited by 31 (2 self)
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grammar in linear time, providing the power and flexibility of a backtracking recursive descent parser without the attendant risk of exponential parse time. A packrat parser can recognize any LL($k$) or LR($k$) language, as well as many languages requiring unlimited lookahead that cannot be parsed
Looking Further Ahead Reveals An Even Smaller World
, 2004
"... We improve Kleinberg’s original greedy routing algorithm, and show that if each node can look ahead log k log n depth of its longrange contacts, the routing path can be found with expected length of O(log n log k log n), where n is the size of the network and k is the number of longrange contacts ..."
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We improve Kleinberg’s original greedy routing algorithm, and show that if each node can look ahead log k log n depth of its longrange contacts, the routing path can be found with expected length of O(log n log k log n), where n is the size of the network and k is the number of longrange contacts
ficient Implementation of Reid's Multiple ypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking
"... AbstractAn efficient implementation of Reid's multiple hypothesis tracking (MHT) algorithm is presented in which the kbest hypotheses are determined in polynomial time using an algorithm due to MurQ [24]. The MHT algorithm is then applied to several motion sequences. The MHT capabilities of t ..."
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function of lookahead (tree depth) indicates that high accuracy can be obtained for tree depths as shallow as three. Experimental results suggest that a realtime MHT solution to the motion correspondence problem is possible for certain classes of scenes. Index TermsMultiple hypothesis tracking, motion