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Markov Logic Networks

by Matthew Richardson, Pedro Domingos - MACHINE LEARNING , 2006
"... We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
Abstract - Cited by 816 (39 self) - Add to MetaCart
learned from relational databases by iteratively optimizing a pseudo-likelihood measure. Optionally, additional clauses are learned using inductive logic programming techniques. Experiments with a real-world database and knowledge base in a university domain illustrate the promise of this approach.

The Temporal Query Language TQuel

by Richard Snodgrass, Santiago Gomez, Richard Snodgrass, Santiago Gomez - ACM Transactions on Database Systems , 1987
"... This paper defines aggregates in the temporal query language TQuel and provides their rormal semantics in the tuple relational calculus. A rormal semantics (or Que! aggregates is defined in the process. Multiple aggregates; aggregates appearing in the where, when, valid, and as-or clauses; nested ag ..."
Abstract - Cited by 332 (45 self) - Add to MetaCart
This paper defines aggregates in the temporal query language TQuel and provides their rormal semantics in the tuple relational calculus. A rormal semantics (or Que! aggregates is defined in the process. Multiple aggregates; aggregates appearing in the where, when, valid, and as-or clauses; nested

Logic Programming in a Fragment of Intuitionistic Linear Logic

by Joshua S. Hodas, Dale Miller , 1994
"... When logic programming is based on the proof theory of intuitionistic logic, it is natural to allow implications in goals and in the bodies of clauses. Attempting to prove a goal of the form D ⊃ G from the context (set of formulas) Γ leads to an attempt to prove the goal G in the extended context Γ ..."
Abstract - Cited by 340 (44 self) - Add to MetaCart
When logic programming is based on the proof theory of intuitionistic logic, it is natural to allow implications in goals and in the bodies of clauses. Attempting to prove a goal of the form D ⊃ G from the context (set of formulas) Γ leads to an attempt to prove the goal G in the extended context Γ

Constructions at Work: The Nature of Generalization in Language

by Adele E Goldberg , 2006
"... Adele Goldberg's Constructions at work is a welcome sequel to her (1995) Constructions, by now a landmark in linguistics. The new book extends her previous analyses and explores new and exciting territories. Since G is arguably the leading figure in Construction Grammar currently, the theory is ..."
Abstract - Cited by 317 (5 self) - Add to MetaCart
. Constructions are form-function pairings, and the idea is that grammar is "constructions all the way down " (p. 18). In other words, clause-level syntactic constructions, phrases, collocations, words, and morphemes are all analyzed in a similar, "construction " fashion. In addition

Additive versus multiplicative clause weighting for SAT

by John Thornton, Duc Nghia Pham, Stuart Bain, Valnir Ferreira - In Proceedings of the 19th AAAI , 2004
"... This paper examines the relative performance of additive and multiplicative clause weighting schemes for propositional satisfiability testing. Starting with one of the most recently developed multiplicative algorithms (SAPS), an experimental study was constructed to isolate the effects of multiplica ..."
Abstract - Cited by 29 (10 self) - Add to MetaCart
This paper examines the relative performance of additive and multiplicative clause weighting schemes for propositional satisfiability testing. Starting with one of the most recently developed multiplicative algorithms (SAPS), an experimental study was constructed to isolate the effects

Towards understanding and harnessing the potential of clause learning

by Paul Beame, Henry Kautz, Ashish Sabharwal - Journal of Artificial Intelligence Research , 2004
"... Efficient implementations of DPLL with the addition of clause learning are the fastest complete Boolean satisfiability solvers and can handle many significant real-world problems, such as verification, planning and design. Despite its importance, little is known of the ultimate strengths and limitat ..."
Abstract - Cited by 99 (10 self) - Add to MetaCart
Efficient implementations of DPLL with the addition of clause learning are the fastest complete Boolean satisfiability solvers and can handle many significant real-world problems, such as verification, planning and design. Despite its importance, little is known of the ultimate strengths

Understanding the power of clause learning

by Paul Beame, Henry Kautz, Ashish Sabharwal - In: Proceedings of the 18th International Joint Conference on Artificial Intelligence , 2003
"... Efficient implementations of DPLL with the addition of clause learning are the fastest complete satisfiability solvers and can handle many significant real-world problems, such as verification, planning, and design. Despite its importance, little is known of the ultimate strengths and limitations of ..."
Abstract - Cited by 25 (4 self) - Add to MetaCart
Efficient implementations of DPLL with the addition of clause learning are the fastest complete satisfiability solvers and can handle many significant real-world problems, such as verification, planning, and design. Despite its importance, little is known of the ultimate strengths and limitations

Binary clause reasoning in QBF

by Horst Samulowitz, Fahiem Bacchus - In Proc. of SAT , 2006
"... Abstract. Binary clause reasoning has found some successful applications in SAT, and it is natural to investigate its use in various extensions of SAT. In this paper we investigate the use of binary clause reasoning in the context of solving Quantified Boolean Formulas (QBF). We develop a DPLL based ..."
Abstract - Cited by 23 (2 self) - Add to MetaCart
based QBF solver that employs extended binary clause reasoning (hyper-binary resolution) to infer new binary clauses both before and during search. These binary clauses are used to discover additional forced literals, as well as to perform equality reduction. Both of these transformations simplify

Extended Clause Learning

by Jinbo Huang , 2010
"... The past decade has seen clause learning as the most successful algorithm for SAT instances arising from real-world applications. This practical success is accompanied by theoretical results showing clause learning as equivalent in power to resolution. There exist, however, problems that are intract ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
The past decade has seen clause learning as the most successful algorithm for SAT instances arising from real-world applications. This practical success is accompanied by theoretical results showing clause learning as equivalent in power to resolution. There exist, however, problems

Soundness of inprocessing in clause . . .

by Norbert Manthey, Tobias Philipp, Christoph Wernhard
"... We present a formalism that models the computation of clause sharing portfolio solvers with inprocessing. The soundness of these solvers is not a straightforward property since shared clauses can make a formula unsatisfiable. Therefore, we develop characterizations of simpli-fication techniques and ..."
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and suggest various settings how clause sharing and inprocessing can be combined. Our formalization models most of the re-cent implemented portfolio systems and we indicate possibilities to im-prove these. A particular improvement is a novel way to combine clause addition techniques – like blocked clause
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