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40
Anytime heuristic search
 Journal of Artificial Intelligence Research (JAIR
, 2007
"... We describe how to convert the heuristic search algorithm A * into an anytime algorithm that finds a sequence of improved solutions and eventually converges to an optimal solution. The approach we adopt uses weighted heuristic search to find an approximate solution quickly, and then continues the we ..."
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Cited by 60 (3 self)
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We describe how to convert the heuristic search algorithm A * into an anytime algorithm that finds a sequence of improved solutions and eventually converges to an optimal solution. The approach we adopt uses weighted heuristic search to find an approximate solution quickly, and then continues the weighted search to find improved solutions as well as to improve a bound on the suboptimality of the current solution. When the time available to solve a search problem is limited or uncertain, this creates an anytime heuristic search algorithm that allows a flexible tradeoff between search time and solution quality. We analyze the properties of the resulting Anytime A * algorithm, and consider its performance in three domains; slidingtile puzzles, STRIPS planning, and multiple sequence alignment. To illustrate the generality of this approach, we also describe how to transform the memoryefficient search algorithm Recursive BestFirst Search (RBFS) into an anytime algorithm. 1.
Divideandconquer frontier search applied to optimal sequence alignment
 In National Conference on Artificial Intelligence (AAAI
, 2000
"... We present a new algorithm that reduces the space complexity of heuristic search. It is most e ective for problem spaces that grow polynomially with problem size, but contain large numbers of short cycles. For example, the problem of nding an optimal global alignment ofseveral DNA or aminoacid sequ ..."
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Cited by 52 (6 self)
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We present a new algorithm that reduces the space complexity of heuristic search. It is most e ective for problem spaces that grow polynomially with problem size, but contain large numbers of short cycles. For example, the problem of nding an optimal global alignment ofseveral DNA or aminoacid sequences can be solved by nding a lowestcost cornertocorner path in a ddimensional grid. A previous algorithm, called divideandconquer bidirectional search (Korf 1999), saves memory by storing only the Open lists and not the Closed lists. We show that this idea can be applied in a unidirectional search aswell. This extends the technique to problems where bidirectional search is not applicable, and is more e cient in both time and space than the bidirectional version. If n is the length of the strings, and d is the number of strings, this algorithm can reduce the memory requirement from O(n d) to O(n d;1). While our current implementation of DCFS is somewhat slower than existing dynamic programming approaches for optimal alignment of multiple gene sequences, DCFS is a more general algorithm 1
Reducing metric sensitivity in randomized trajectory design
 In IEEE/RSJ Int. Conf. on Intelligent Robots & Systems
, 2001
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Combining SpeedUp Techniques for ShortestPath Computations
 In Proc. 3rd Workshop on Experimental and Efficient Algorithms. LNCS
, 2004
"... Computing a shortest path from one node to another in a directed graph is a very common task in practice. This problem is classically solved by Dijkstra's algorithm. Many techniques are known to speed up this algorithm heuristically, while optimality of the solution can still be guaranteed. ..."
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Cited by 29 (7 self)
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Computing a shortest path from one node to another in a directed graph is a very common task in practice. This problem is classically solved by Dijkstra's algorithm. Many techniques are known to speed up this algorithm heuristically, while optimality of the solution can still be guaranteed. In most studies, such techniques are considered individually.
SpeedUp Techniques for ShortestPath Computations
 IN PROCEEDINGS OF THE 24TH INTERNATIONAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE (STACS’07
, 2007
"... During the last years, several speedup techniques for Dijkstra’s algorithm have been published that maintain the correctness of the algorithm but reduce its running time for typical instances. They are usually based on a preprocessing that annotates the graph with additional information which can ..."
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Cited by 20 (6 self)
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During the last years, several speedup techniques for Dijkstra’s algorithm have been published that maintain the correctness of the algorithm but reduce its running time for typical instances. They are usually based on a preprocessing that annotates the graph with additional information which can be used to prune or guide the search. Timetable information in public transport is a traditional application domain for such techniques. In this paper, we provide a condensed overview of new developments and extensions of classic results. Furthermore, we discuss how combinations of speedup techniques can be realized to take advantage from different strategies.
Discovering Correlated SpatioTemporal Changes in Evolving Graphs
 UNDER CONSIDERATION FOR PUBLICATION IN KNOWLEDGE AND INFORMATION SYSTEMS
, 2007
"... Graphs provide powerful abstractions of relational data, and are widely used in fields such as network management, web page analysis and sociology. While many graph representations of data describe dynamic and time evolving relationships, most graph mining work treats graphs as static entities. Our ..."
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Cited by 13 (3 self)
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Graphs provide powerful abstractions of relational data, and are widely used in fields such as network management, web page analysis and sociology. While many graph representations of data describe dynamic and time evolving relationships, most graph mining work treats graphs as static entities. Our focus in this paper is to discover regions of a graph that are evolving in a similar manner. To discover regions of correlated spatiotemporal change in graphs, we propose an algorithm called cSTAG. Whereas most clustering techniques are designed to find clusters that optimise a single distance measure, cSTAG addresses the problem of finding clusters that optimise both temporal and spatial distance measures simultaneously. We show the effectiveness of cSTAG using a quantitative analysis of accuracy on synthetic data sets, as well as demonstrating its utility on two large, reallife data sets, where one is the routing topology of the Internet, and the other is the dynamic graph of files accessed together on the 1998 World Cup official website.
Partial pattern databases
"... Abstract. Perimeters and pattern databases are two similar memorybased techniques used in singleagent search problems. We present partial pattern databases, which unify the two approaches into a single memorybased heuristic table. Our approach allows the use of any abstraction level. We achieve a t ..."
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Cited by 9 (1 self)
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Abstract. Perimeters and pattern databases are two similar memorybased techniques used in singleagent search problems. We present partial pattern databases, which unify the two approaches into a single memorybased heuristic table. Our approach allows the use of any abstraction level. We achieve a threefold reduction in the average number of nodes generated on the 13pancake puzzle and a 27 % reduction on the 15puzzle. 1
Crowdscale interactive formal reasoning and analytics
 In UIST
, 2013
"... Large online courses often assign problems that are gradable by simple checks such as multiple choice, but these checks are inappropriate for domains in which students may produce an infinity of correct solutions. One such domain is derivations: sequences of logical steps commonly used in assignmen ..."
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Cited by 7 (1 self)
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Large online courses often assign problems that are gradable by simple checks such as multiple choice, but these checks are inappropriate for domains in which students may produce an infinity of correct solutions. One such domain is derivations: sequences of logical steps commonly used in assignments for technical, mathematical and scientific subjects. We present DeduceIt, a system for creating, grading, and analyzing derivation assignments across arbitrary formal domains. DeduceIt supports assignments in any logical formalism, provides students with incremental feedback, and aggregates student paths through each proof to produce instructor analytics. DeduceIt benefits from checking thousands of derivations on the web: it introduces a proof cache, a novel data structure which leverages a crowd of students to decrease the cost of checking derivations and providing realtime, constructive feedback. We evaluate DeduceIt with 990 students in an online compilers course, finding students take advantage of its incremental feedback and instructors benefit from its structured insights into confusing course topics. Our work suggests that automated reasoning can extend online assignments and largescale education to many new domains. Author Keywords MOOC, theorem prover, formal logic, online education
Finding optimal solutions to Atomix
 KI 2001: ADVANCES IN ARTIFICIAL INTELLIGENCE, VOLUME 2174 OF LNCS/LNAI
, 2001
"... We present solutions of benchmark instances to the solitaire computer game Atomix found with different heuristic search methods. The problem is PSPACEcomplete. An implementation of the heuristic algorithm A * is presented that needs no priority queue, thereby having very low memory overhead. The li ..."
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Cited by 6 (5 self)
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We present solutions of benchmark instances to the solitaire computer game Atomix found with different heuristic search methods. The problem is PSPACEcomplete. An implementation of the heuristic algorithm A * is presented that needs no priority queue, thereby having very low memory overhead. The limited memory algorithm IDA * is handicapped by the fact that, due to move transpositions, duplicates appear very frequently in the problem space; several schemes of using memory to mitigate this weakness are explored, among those, “partial” schemes which trade memory savings for a small probability of not finding an optimal solution. Even though the underlying search graph is directed, backward search is shown to be viable, since the branching factor can be proven to be the same as for forward search.