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695
Conflictdriven answer set solving
 in Proceedings IJCAI’07
, 2007
"... We introduce a new approach to computing answer sets of logic programs, based on concepts from constraint processing (CSP) and satisfiability checking (SAT). The idea is to view inferences in answer set programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraintbased ..."
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Cited by 204 (49 self)
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We introduce a new approach to computing answer sets of logic programs, based on concepts from constraint processing (CSP) and satisfiability checking (SAT). The idea is to view inferences in answer set programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraintbased framework for the different kinds of inferences in ASP. It also allows us to apply advanced techniques from the areas of CSP and SAT. We have implemented our approach in the new ASP solver clasp. Our experiments show that the approach is competitive with stateoftheart ASP solvers. 1
A Scalable Method for Multiagent Constraint Optimization
"... We present in this paper a new, complete method for distributed constraint optimization, based on dynamic programming. It is a utility propagation method, inspired by the sumproduct algorithm, which is correct only for treeshaped constraint networks. In this paper, we show how to extend that algor ..."
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Cited by 179 (18 self)
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We present in this paper a new, complete method for distributed constraint optimization, based on dynamic programming. It is a utility propagation method, inspired by the sumproduct algorithm, which is correct only for treeshaped constraint networks. In this paper, we show how to extend that algorithm to arbitrary topologies using a pseudotree arrangement of the problem graph. Our algorithm requires a linear number of messages, whose maximal size depends on the induced width along the particular pseudotree chosen. We compare our algorithm with backtracking algorithms, and present experimental results. For some problem types we report orders of magnitude fewer messages, and the ability to deal with arbitrarily large problems. Our algorithm is formulated for optimization problems, but can be easily applied to satisfaction problems as well.
AND/OR Search Spaces for Graphical Models
, 2004
"... The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays some of the independencies present in the gr ..."
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Cited by 126 (47 self)
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The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays some of the independencies present in the graphical model explicitly and may sometime reduce the search space exponentially. Indeed, most
Minion: A fast scalable constraint solver
 In: Proceedings of ECAI 2006, Riva del Garda
, 2006
"... Abstract. We present Minion, a new constraint solver. Empirical results on standard benchmarks show orders of magnitude performance gains over stateoftheart constraint toolkits. These gains increase with problem size – Minion delivers scalable constraint solving. Minion is a generalpurpose const ..."
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Cited by 118 (39 self)
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Abstract. We present Minion, a new constraint solver. Empirical results on standard benchmarks show orders of magnitude performance gains over stateoftheart constraint toolkits. These gains increase with problem size – Minion delivers scalable constraint solving. Minion is a generalpurpose constraint solver, with an expressive input language based on the common constraint modelling device of matrix models. Focussing on matrix models supports a highlyoptimised implementation, exploiting the properties of modern processors. This contrasts with current constraint toolkits, which, in order to provide ever more modelling and solving options, have become progressively more complex at the cost of both performance and usability. Minion is a black box from the user point of view, deliberately providing few options. This, combined with its raw speed, makes Minion a substantial step towards Puget’s ‘Model and Run ’ constraint solving paradigm. 1
Simple Search Methods for Finding a Nash Equilibrium
 Games and Economic Behavior
, 2004
"... We present two simple search methods for computing a sample Nash equilibrium in a normalform game: one for 2player games and one for nplayer games. We test these algorithms on many classes of games, and show that they perform well against the state of the art the LemkeHowson algorithm for ..."
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Cited by 110 (3 self)
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We present two simple search methods for computing a sample Nash equilibrium in a normalform game: one for 2player games and one for nplayer games. We test these algorithms on many classes of games, and show that they perform well against the state of the art the LemkeHowson algorithm for 2player games, and Simplicial Subdivision and GovindanWilson for nplayer games.
Learning DependencyBased Compositional Semantics
"... Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of the target logical forms. In this paper, we learn to map questions to answers via latent logical forms, which are induced ..."
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Cited by 110 (9 self)
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Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of the target logical forms. In this paper, we learn to map questions to answers via latent logical forms, which are induced automatically from questionanswer pairs. In tackling this challenging learning problem, we introduce a new semantic representation which highlights a parallel between dependency syntax and efficient evaluation of logical forms. On two standard semantic parsing benchmarks (GEO and JOBS), our system obtains the highest published accuracies, despite requiring no annotated logical forms. 1
Networked Distributed POMDPs: A Synthesis of Distributed Constraint Optimization and POMDPs
, 2005
"... In many realworld multiagent applications such as distributed sensor nets, a network of agents is formed based on each agent’s limited interactions with a small number of neighbors. While distributed POMDPs capture the realworld uncertainty in multiagent domains, they fail to exploit such locality ..."
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Cited by 96 (20 self)
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In many realworld multiagent applications such as distributed sensor nets, a network of agents is formed based on each agent’s limited interactions with a small number of neighbors. While distributed POMDPs capture the realworld uncertainty in multiagent domains, they fail to exploit such locality of interaction. Distributed constraint optimization (DCOP) captures the locality of interaction but fails to capture planning under uncertainty. This paper present a new model synthesized from distributed POMDPs and DCOPs, called Networked Distributed POMDPs (NDPOMDPs). Exploiting network structure enables us to present two novel algorithms for NDPOMDPs: a distributed policy generation algorithm that performs local search and a systematic policy search that is guaranteed to reach the global optimal.
Dependency parsing by belief propagation
 In Proceedings of EMNLP
, 2008
"... We formulate dependency parsing as a graphical model with the novel ingredient of global constraints. We show how to apply loopy belief propagation (BP), a simple and effective tool for approximate learning and inference. As a parsing algorithm, BP is both asymptotically and empirically efficient. E ..."
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Cited by 85 (9 self)
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We formulate dependency parsing as a graphical model with the novel ingredient of global constraints. We show how to apply loopy belief propagation (BP), a simple and effective tool for approximate learning and inference. As a parsing algorithm, BP is both asymptotically and empirically efficient. Even with secondorder features or latent variables, which would make exact parsing considerably slower or NPhard, BP needs only O(n3) time with a small constant factor. Furthermore, such features significantly improve parse accuracy over exact firstorder methods. Incorporating additional features would increase the runtime additively rather than multiplicatively. 1
Conjunctive Queries over Trees
, 2004
"... We study the complexity and expressive power of conjunctive queries over unranked labeled trees, where the tree structures are represented using âaxis relationsâ such as âchildâ, âdescendantâ, and âfollowingâ (we consider a superset of the XPath axes) as well as unary relations for n ..."
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Cited by 84 (8 self)
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We study the complexity and expressive power of conjunctive queries over unranked labeled trees, where the tree structures are represented using âaxis relationsâ such as âchildâ, âdescendantâ, and âfollowingâ (we consider a superset of the XPath axes) as well as unary relations for node labels. (Cyclic) conjunctive queries over trees occur in a wide range of data management scenarios related to XML, the Web, and computational linguistics. We establish a framework for characterizing structures representing trees for which conjunctive queries can be evaluated efficiently. Then we completely chart the tractability frontier of the problem for our axis relations, i.e., we find all subsetmaximal sets of axes for which query evaluation is in polynomial time. All polynomialtime results are obtained immediately using the proof techniques from our framework. Finally, we study the expressiveness of conjunctive queries over trees and compare it to the expressive power of fragments of XPath. We show that for each conjunctive query, there is an equivalent acyclic positive query (i.e., a set of acyclic conjunctive queries), but that in general this query is not of polynomial size.
Constraint propagation
 Handbook of Constraint Programming
, 2006
"... Constraint propagation is a form of inference, not search, and as such is more ”satisfying”, both technically and aesthetically. —E.C. Freuder, 2005. Constraint reasoning involves various types of techniques to tackle the inherent ..."
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Cited by 77 (5 self)
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Constraint propagation is a form of inference, not search, and as such is more ”satisfying”, both technically and aesthetically. —E.C. Freuder, 2005. Constraint reasoning involves various types of techniques to tackle the inherent