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Partial Constraint Satisfaction
, 1992
"... . A constraint satisfaction problem involves finding values for variables subject to constraints on which combinations of values are allowed. In some cases it may be impossible or impractical to solve these problems completely. We may seek to partially solve the problem, in particular by satisfying ..."
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Cited by 469 (21 self)
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. A constraint satisfaction problem involves finding values for variables subject to constraints on which combinations of values are allowed. In some cases it may be impossible or impractical to solve these problems completely. We may seek to partially solve the problem, in particular by satisfying
Algorithms for ConstraintSatisfaction Problems: A Survey
, 1992
"... A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraintsatisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments, an ..."
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Cited by 447 (0 self)
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A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraintsatisfaction problem. Some examples are machine vision, belief maintenance, scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments
Do investmentcash flow sensitivities provide useful measures of financing constraints?
 QUARTERLY JOURNAL OF ECONOMICS
, 1997
"... No. This paper investigates the relationship between financing constraints and investmentcash flow sensitivities by analyzing the firms identified by Fazzari, Hubbard, and Petersen as having unusually high investmentcash flow sensitivities. We Quarterlynd that firms that appear less Quarterlynanci ..."
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Cited by 656 (8 self)
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No. This paper investigates the relationship between financing constraints and investmentcash flow sensitivities by analyzing the firms identified by Fazzari, Hubbard, and Petersen as having unusually high investmentcash flow sensitivities. We Quarterlynd that firms that appear less
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
 ARTIF. INTELL
, 1992
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueorderin ..."
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Cited by 458 (6 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value
Where the REALLY Hard Problems Are
 IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI91),VOLUME 1
, 1991
"... It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard p ..."
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Cited by 681 (1 self)
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It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard
A Note on the Confinement Problem
, 1973
"... This not explores the problem of confining a program during its execution so that it cannot transmit information to any other program except its caller. A set of examples attempts to stake out the boundaries of the problem. Necessary conditions for a solution are stated and informally justified. ..."
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Cited by 532 (0 self)
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This not explores the problem of confining a program during its execution so that it cannot transmit information to any other program except its caller. A set of examples attempts to stake out the boundaries of the problem. Necessary conditions for a solution are stated and informally justified.
The Symbol Grounding Problem
, 1990
"... There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the "symbol grounding problem": How can the semantic interpretation of a formal symbol system be m ..."
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Cited by 1072 (18 self)
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There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the "symbol grounding problem": How can the semantic interpretation of a formal symbol system
On Constraint Problems with Incomplete
 Principles and Practice of Constraint Programming, number 2470 in LNCS
, 2002
"... Realworld constraint problems abound with uncertainty. Problems with incomplete or erroneous data are often simplified at present to tractable deterministic models, or modified using error correction methods, with the aim of seeking a solution. However, this can lead us to solve the wrong problem b ..."
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Realworld constraint problems abound with uncertainty. Problems with incomplete or erroneous data are often simplified at present to tractable deterministic models, or modified using error correction methods, with the aim of seeking a solution. However, this can lead us to solve the wrong problem
Imprecise Soft Constraint Problems
"... Abstract. We define intervalvalued soft constraints, where users can associate an interval of preference values, rather than a single value, to each instantiation of the variables of the constraints. This allows us to model a form of uncertainty and imprecision that is often found in reallife prob ..."
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life problems. We then define several notions of optimal solutions for such problems, providing algorithms to find optimals and also to test whether a solution is optimal. Besides the usefulness of the algorithms, that can be the base for an environment where to reason with uncertainty in soft constraints
House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle
, 2002
"... I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents ’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move asse ..."
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Cited by 496 (10 self)
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I develop a general equilibrium model with sticky prices, credit constraints, nominal loans and asset prices. Changes in asset prices modify agents ’ borrowing capacity through collateral value; changes in nominal prices affect real repayments through debt deflation. Monetary policy shocks move
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