Journal articles: 'Consistency constraints'

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Nagarajan, S., S. D. Goodwin, and A. Sattar. "Extending Dual Arc Consistency." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 05 (August 2003): 781–815. http://dx.doi.org/10.1142/s0218001403002654.

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Many extensions to existing binary constraint satisfaction algorithms have been proposed that directly deal with nonbinary constraints. Another choice is to perform a structural transformation of the representation of the problem, so that the resulting problem is a binary CSP except that now the original constraints which were nonbinary are replaced by binary compatibility constraints between relations. A lot of recent work has focussed on comparing different levels of local consistency enforceable in the nonbinary representation with the dual representation. In this paper we present extensions to the standard dual encoding that can compactly represent the given CSP using an equivalent dual encoding that contains all the original solutions to the CSP, using constraint coverings. We show how enforcing arc consistency in these constraint covering based encodings, strictly dominates enforcement of generalized arc consistency (GAC) on the primal nonbinary encoding.

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Zhang, Y., and R. H. C. Yap. "Set Intersection and Consistency in Constraint Networks." Journal of Artificial Intelligence Research 27 (December 13, 2006): 441–64. http://dx.doi.org/10.1613/jair.2058.

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In this paper, we show that there is a close relation between consistency in a constraint network and set intersection. A proof schema is provided as a generic way to obtain consistency properties from properties on set intersection. This approach not only simplifies the understanding of and unifies many existing consistency results, but also directs the study of consistency to that of set intersection properties in many situations, as demonstrated by the results on the convexity and tightness of constraints in this paper. Specifically, we identify a new class of tree convex constraints where local consistency ensures global consistency. This generalizes row convex constraints. Various consistency results are also obtained on constraint networks where only some, in contrast to all in the existing work,constraints are tight.

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Jeavons, Peter, David Cohen, and Martin C. Cooper. "Constraints, consistency and closure." Artificial Intelligence 101, no. 1-2 (May 1998): 251–65. http://dx.doi.org/10.1016/s0004-3702(98)00022-8.

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Lecoutre, Christophe, Anastasia Paparrizou, and Kostas Stergiou. "Extending STR to a Higher-Order Consistency." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 30, 2013): 576–82. http://dx.doi.org/10.1609/aaai.v27i1.8622.

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One of the most widely studied classes of constraints in constraint programming (CP) is that of table constraints. Numerousspecialized filtering algorithms, enforcing the wellknown property called generalized arc consistency (GAC),have been developed for such constraints. Among the most successful GAC algorithms for table constraints, we find variants of simple tabular reduction (STR), like STR2. In this paper,we propose an extension of STR-based algorithms that achieves full pairwise consistency (FPWC), a consistency stronger than GAC and max restricted pairwise consistency (maxRPWC). Our approach involves counting the number of occurrences of specific combinations of values in constraint intersections. Importantly, the worst-case time complexity of one call to the basic filtering procedure at the heart of our new algorithm is quite close to that of STR algorithms. Experiments demonstrate that our method can outperform STR2 in many classes of problems, being significantly faster in some cases. Also, it is clearly superior to maxRPWC+, an algorithm that has been recently proposed.

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Paparrizou, Anastasia, and Kostas Stergiou. "An Efficient Higher-Order Consistency Algorithm for Table Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 535–41. http://dx.doi.org/10.1609/aaai.v26i1.8135.

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Table constraints are very important in constraint programming as they are present in many real problems from areas such as configuration and databases. As a result, numerous specialized algorithms that achieve generalized arc consistency (GAC) on table constraints have been proposed. Since these algorithms achieve GAC, they operate on one constraint at a time. In this paper we propose an efficient algorithm for table constraints that achieves a stronger local consistency than GAC. This algorithm, called maxRPWC+, is based on the local consistency maxRPWC and allows the efficient handling of intersecting table constraints. Experimental results from benchmark problems demonstrate that maxRPWC+ is clearly more robust than a state-of-the-art GAC algorithm in classes of problems with interleaved table constraints, being orders of magnitude faster in some of these classes.

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Bordeaux, Lucas, Marco Cadoli, and Toni Mancini. "Generalizing consistency and other constraint properties to quantified constraints." ACM Transactions on Computational Logic 10, no. 3 (April 2009): 1–25. http://dx.doi.org/10.1145/1507244.1507247.

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LIU, BING. "SPECIFIC CONSTRAINT HANDLING IN CONSTRAINT SATISFACTION PROBLEMS." International Journal on Artificial Intelligence Tools 03, no. 01 (March 1994): 79–96. http://dx.doi.org/10.1142/s0218213094000066.

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Abundant literatures exist on consistency techniques for solving Constraint Satisfaction Problems (CSPs). These literatures, however, focused mainly on finding efficient general techniques to achieve network consistency and to solve CSPs. So far, many techniques have been reported, e.g., node consistency, arc consistency, path consistency, k-consistency, forward checking, lookahead, partial lookahead, etc. Not enough attention has been given to individual constraints, and how constraint specific features may be exploited for more efficient consistency check. Many types of constraints exist in real problems, and each has its own features. These features may allow specific consistency techniques to be designed such that they are more efficient than the general algorithms. To analyze this issue, we divide a consistency algorithm into three parts: (1) activating constraints for check; (2) selecting the next constraint to be checked; and (3) checking the selected constraint. We will discuss how constraint specific features may influence each of these aspects and how special handling techniques may be designed to improve the efficiency. In order to allow these individual constraint handling techniques to be used, a new consistency algorithm is also proposed.

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Kutach, Douglas N. "Time Travel and Consistency Constraints." Philosophy of Science 70, no. 5 (December 2003): 1098–113. http://dx.doi.org/10.1086/377392.

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Sam-Haroud, D., and B. Faltings. "Consistency techniques for continuous constraints." Constraints 1, no. 1-2 (September 1996): 85–118. http://dx.doi.org/10.1007/bf00143879.

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Cooper, Martin, and Thomas Schiex. "Arc consistency for soft constraints." Artificial Intelligence 154, no. 1-2 (April 2004): 199–227. http://dx.doi.org/10.1016/j.artint.2003.09.002.

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APT, KRZYSZTOF R., and ERIC MONFROY. "Constraint programming viewed as rule-based programming." Theory and Practice of Logic Programming 1, no. 6 (November 2001): 713–50. http://dx.doi.org/10.1017/s1471068401000072.

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We study here a natural situation when constraint programming can be entirely reduced to rule-based programming. To this end we explain first how one can compute on constraint satisfaction problems using rules represented by simple first-order formulas. Then we consider constraint satisfaction problems that are based on predefined, explicitly given constraints. To solve them we first derive rules from these explicitly given constraints and limit the computation process to a repeated application of these rules, combined with labeling. We consider two types of rule here. The first type, that we call equality rules, leads to a new notion of local consistency, called rule consistency that turns out to be weaker than arc consistency for constraints of arbitrary arity (called hyper-arc consistency in Marriott & Stuckey (1998)). For Boolean constraints rule consistency coincides with the closure under the well-known propagation rules for Boolean constraints. The second type of rules, that we call membership rules, yields a rule-based characterization of arc consistency. To show feasibility of this rule-based approach to constraint programming, we show how both types of rules can be automatically generated, as CHR rules of Frühwirth (1995). This yields an implementation of this approach to programming by means of constraint logic programming. We illustrate the usefulness of this approach to constraint programming by discussing various examples, including Boolean constraints, two typical examples of many valued logics, constraints dealing with Waltz's language for describing polyhedral scenes, and Allen's qualitative approach to temporal logic.

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Lee, Jimmy, and K. Leung. "A Stronger Consistency for Soft Global Constraints in Weighted Constraint Satisfaction." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 3, 2010): 121–27. http://dx.doi.org/10.1609/aaai.v24i1.7550.

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Weighted Constraint Satisfaction is made practical by powerful consistency techniques, such as AC*, FDAC* and EDAC*, which reduce search space effectively and efficiently during search, but they are designed for only binary and ternary constraints. To allow soft global constraints, usually of high arity, to enjoy the same benefits, Lee and Leung give polynomial time algorithms to enforce generalized AC* (GAC*) and FDAC* (FDGAC*) for projection-safe soft non-binary constraints. Generalizing the stronger EDAC* is less straightforward. In this paper, we first reveal the oscillation problem when enforcing EDAC* on constraints sharing more than one variable. To avoid oscillation, we propose a weak version of EDAC* and generalize it to weak EDGAC* for non-binary constraints. Weak EDGAC* is stronger than FDGAC* and GAC*, but weaker than VAC and soft k-consistency for k > 2. We also show that weak EDGAC* can be enforced in polynomial time for projection-safe constraints. Extensive experimentation confirms the efficiency of our proposal.

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Yap, Roland H. C., Wei Xia, and Ruiwei Wang. "Generalized Arc Consistency Algorithms for Table Constraints: A Summary of Algorithmic Ideas." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 09 (April 3, 2020): 13590–97. http://dx.doi.org/10.1609/aaai.v34i09.7086.

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Constraint Programming is a powerful paradigm to model and solve combinatorial problems. While there are many kinds of constraints, the table constraint (also called a CSP) is perhaps the most significant—being the most well-studied and has the ability to encode any other constraints defined on finite variables. Thus, designing efficient filtering algorithms on table constraints has attracted significant research efforts. In turn, there have been great improvements in efficiency over time with the evolution and development of AC and GAC algorithms. In this paper, we survey the existing filtering algorithms for table constraint focusing on historically important ideas and recent successful techniques shown to be effective.

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ZHANG, YUANLIN, and ROLAND H. C. YAP. "Solving functional constraints by variable substitution." Theory and Practice of Logic Programming 11, no. 2-3 (February 4, 2011): 297–322. http://dx.doi.org/10.1017/s1471068410000591.

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AbstractFunctional constraints and bi-functional constraints are an important constraint class in Constraint Programming (CP) systems, in particular for Constraint Logic Programming (CLP) systems. CP systems with finite domain constraints usually employ Constraint Satisfaction Problem(s)-based solvers which use local consistency, for example, arc consistency. We introduce a new approach which is based instead on variable substitution. We obtain efficient algorithms for reducing systems involving functional and bi-functional constraints together with other nonfunctional constraints. It also solves globally any CSP where there exists a variable such that any other variable is reachable from it through a sequence of functional constraints. Our experiments on random problems show that variable elimination can significantly improve the efficiency of solving problems with functional constraints.

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15

David, P. "Using Pivot Consistency to Decompose and Solve Functional CSPs." Journal of Artificial Intelligence Research 2 (May 1, 1995): 447–74. http://dx.doi.org/10.1613/jair.167.

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Many studies have been carried out in order to increase thesearch efficiency of constraint satisfaction problems; among them,some make use of structural properties of the constraintnetwork; others take into account semantic properties of theconstraints, generally assuming that all the constraints possessthe given property. In this paper, we propose a new decompositionmethod benefiting from both semantic properties of functional constraints (not bijective constraints) and structuralproperties of the network; furthermore, not all the constraints needto be functional. We show that under some conditions, the existenceof solutions can be guaranteed. We first characterize a particularsubset of the variables, which we name a root set. We thenintroduce pivot consistency, a new local consistency which is aweak form of path consistency and can be achieved in O(n^2d^2)complexity (instead of O(n^3d^3) for path consistency), and wepresent associated properties; in particular, we show that anyconsistent instantiation of the root set can be linearly extended to a solution, which leads to the presentation of the aforementioned new method for solving by decomposing functional CSPs.

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Ma, H., and K. G. Shin. "Checking Consistency in Multimedia Synchronization Constraints." IEEE Transactions on Multimedia 6, no. 4 (August 2004): 565–74. http://dx.doi.org/10.1109/tmm.2004.830807.

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17

Feher, A. "Brightness Illusion Induced by Consistency Constraints." Perception 26, no. 1_suppl (August 1997): 140. http://dx.doi.org/10.1068/v970071.

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We present a novel brightness illusion (the ‘Brick Illusion’) that is determined by perceptual interpretation. The image is ambiguous in terms of depth layering, and the strength of the illusion depends on the chosen interpretation. When a certain interpretation is enforced by stereo disparity, and the layering is disambiguated, the strength of the illusion changes according to constraints on the consistency between depth layering, transparency relationships, and surface brightness. We applied a 2AFC brightness comparison procedure to quantify the strength of the illusion. This procedure allowed us to measure the uncertainty of judgements on relative surface brightness in illusory conditions. The increased uncertainty of our observers among these conditions reflects the multidimensional nature of these judgements. This paper is linked to the following World Wide Web page: http://zeus.rutgers.edu/∼feher/brick.html . With a Java-enabled browser the reader can change the gray levels of the backgrounds and the disks, the disparity of the disks, and other parameters.

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Shrauner, J. Ely. "Gluon mass and gauge consistency constraints." Journal of Physics G: Nuclear and Particle Physics 19, no. 7 (July 1, 1993): 979–86. http://dx.doi.org/10.1088/0954-3899/19/7/008.

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Horna, S., D. Meneveaux, G. Damiand, and Y. Bertrand. "Consistency constraints and 3D building reconstruction." Computer-Aided Design 41, no. 1 (January 2009): 13–27. http://dx.doi.org/10.1016/j.cad.2008.11.006.

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Jiang, Tao, and Weihong Zhou. "An Approach of Defining Domain Constraints for Domain-Specific Modeling Language." International Journal of Pattern Recognition and Artificial Intelligence 35, no. 09 (April 10, 2021): 2153002. http://dx.doi.org/10.1142/s0218001421530025.

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Many Domain-Specific Modeling Languages (DSML) cannot formally define their semantics, leading to difficulties in identifying user-defined domain constraints. In this study, we propose a user-defined mechanism of domain constraints based on the formalization of structural semantics of DSML. First, we formally define concepts and decision methods of consistency and validity of domain constraints. Subsequently, we establish concepts and reasoning methods of domain-based model consistency. Thus, several domain constraint instances are defined and different models instances’ consistency are reasoned based on formalization of software architecture domain metamodel to illustrate our approach. Finally, our formal definition mechanism of domain constraint is added to our automatic translator for formalizing DSML and its models to automatically reason about domain constraints built based on DSML.

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Planken, Léon, Mathijs De Weerdt, and Neil Yorke-Smith. "Incrementally Solving STNs by Enforcing Partial Path Consistency." Proceedings of the International Conference on Automated Planning and Scheduling 20 (May 25, 2021): 129–36. http://dx.doi.org/10.1609/icaps.v20i1.13417.

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Efficient management and propagation of temporal constraints is important for temporal planning as well as for scheduling. During plan development, new events and temporal constraints are added and existing constraints may be tightened; the consistency of the whole temporal network is frequently checked; and results of constraint propagation guide further search. Recent work shows that enforcing partial path consistency provides an efficient means of propagating temporal information for the popular Simple Temporal Network (STN). We show that partial path consistency can be enforced incrementally, thus exploiting the similarities of the constraint network between subsequent edge tightenings. We prove that the worst-case time complexity of our algorithm can be bounded both by the number of edges in the chordal graph (which is better than the previous bound of the number of vertices squared), and by the degree of the chordal graph times the number of vertices incident on updated edges. We show that for many sparse graphs, the latter bound is better than that of the previously best-known approaches. In addition, our algorithm requires space only linear in the number of edges of the chordal graph, whereas earlier work uses space quadratic in the number of vertices. Finally, empirical results show that when incrementally solving sparse STNs, stemming from problems such as Hierarchical Task Network planning, our approach outperforms extant algorithms.

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Roy, Pierre, and Francois Pachet. "Enforcing Meter in Finite-Length Markov Sequences." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 30, 2013): 854–61. http://dx.doi.org/10.1609/aaai.v27i1.8661.

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Markov processes are increasingly used to generate finite-length sequences that imitate a given style. However, Markov processes are notoriously difficult to control. Recently, Markov constraints have been introduced to give users some control on generated sequences. Markov constraints reformulate finite-length Markov sequence generation in the framework of constraint satisfaction (CSP). However, in practice, this approach is limited to local constraints and its performance is low for global constraints, such as cardinality or arithmetic constraints. This limitation prevents generated sequences to follow structural properties which are independent of the style, but inherent to the domain, such as meter. In this article, we introduce meter, a constraint that ensures a sequence is 1) Markovian with regards to a given corpus and 2) follows metrical rules expressed as cumulative cost functions. Additionally, meter can simultaneously enforce cardinality constraints. We propose a domain consistency algorithm whose complexity is pseudo-polynomial. This result is obtained thanks to a theorem on the growth of sumsets by Khovanskii. We illustrate our constraint on meter-constrained music generation problems that were so far not solvable by any other technique.

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Rodrigues Quemel e Assis Santana, Pedro, and Brian Williams. "Chance-Constrained Consistency for Probabilistic Temporal Plan Networks." Proceedings of the International Conference on Automated Planning and Scheduling 24 (May 11, 2014): 271–79. http://dx.doi.org/10.1609/icaps.v24i1.13651.

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Unmanned deep-sea and planetary vehicles operate in highly uncertain environments. Autonomous agents often are not adopted in these domains due to the risk of mission failure, and loss of vehicles. Prior work on contingent plan execution addresses this issue by placing bounds on uncertain variables and by providing consistency guarantees for a `worst-case' analysis, which tends to be too conservative for real-world applications. In this work, we unify features from trajectory optimization through risk-sensitive execution methods and high-level, contingent plan execution in order to extend existing guarantees of consistency for conditional plans to a chance-constrained setting. The result is a set of efficient algorithms for computing plan execution policies with explicit bounds on the risk of failure. To accomplish this, we introduce Probabilistic Temporal Plan Network (pTPN), which improve previous formulations, by incorporating probabilistic uncertainty and chance-constraints into the plan representation. We then introduce a novel method to the chance-constrained strong consistency problem, by leveraging a conflict-directed approach that searches for an execution policy that maximizes reward while meeting the risk constraint. Experimental results indicate that our approach for computing strongly consistent policies has an average scalability gain of about one order of magnitude, when compared to current methods based on chronological search.

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Caroprese, L., S. Greco, and E. Zumpano. "Active Integrity Constraints for Database Consistency Maintenance." IEEE Transactions on Knowledge and Data Engineering 21, no. 7 (July 2009): 1042–58. http://dx.doi.org/10.1109/tkde.2008.226.

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Haque, Sheikh Mohammadul, Gautam P. Pai, and Venu Madhav Govindu. "Symmetric Smoothing Filters From Global Consistency Constraints." IEEE Transactions on Image Processing 24, no. 5 (May 2015): 1536–48. http://dx.doi.org/10.1109/tip.2014.2383316.

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Bhattacharjee, A., and Y. Yuan. "Self-Consistency Constraints on the Dynamo Mechanism." Astrophysical Journal 449 (August 1995): 739. http://dx.doi.org/10.1086/176094.

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Kopetz, H., and K. Kim. "Consistency Constraints in Distributed Real Time Systems." IFAC Proceedings Volumes 21, no. 12 (September 1988): 29–34. http://dx.doi.org/10.1016/b978-0-08-036938-9.50010-8.

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Zghidi, Imen, Brahim Hnich, and Abdelwaheb Rebai. "Introducing statistical consistency for infinite chance constraints." Annals of Mathematics and Artificial Intelligence 83, no. 2 (January 11, 2018): 165–81. http://dx.doi.org/10.1007/s10472-018-9572-3.

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Skiadopoulos, Spiros, and Manolis Koubarakis. "On the consistency of cardinal direction constraints." Artificial Intelligence 163, no. 1 (March 2005): 91–135. http://dx.doi.org/10.1016/j.artint.2004.10.010.

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Paparrizou, Anastasia, and Kostas Stergiou. "Strong local consistency algorithms for table constraints." Constraints 21, no. 2 (January 30, 2015): 163–97. http://dx.doi.org/10.1007/s10601-014-9179-1.

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Wang, Huaijun, Dandan Du, Junhuai Li, Wenchao Ji, and Lei Yu. "A Cyclic Consistency Motion Style Transfer Method Combined with Kinematic Constraints." Journal of Sensors 2021 (June 29, 2021): 1–17. http://dx.doi.org/10.1155/2021/5548614.

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Motion capture technology plays an important role in the production field of film and television, animation, etc. In order to reduce the cost of data acquisition and improve the reuse rate of motion capture data and the effect of movement style migration, the synthesis technology of motion capture data in human movement has become a research hotspot in this field. In this paper, kinematic constraints (KC) and cyclic consistency (CC) network are employed to study the methods of kinematic style migration. Firstly, cycle-consistent adversarial network (CCycleGAN) is constructed, and the motion style migration network based on convolutional self-encoder is used as a generator to establish the cyclic consistent constraint between the generated motion and the content motion, so as to improve the action consistency between the generated motion and the content motion and eliminate the lag phenomenon of the generated motion. Then, kinematic constraints are introduced to normalize the movement generation, so as to solve the problems such as jitter and sliding step in the movement style migration results. Experimental results show that the generated motion of the cyclic consistent style transfer method with kinematic constraints is more similar to the style of style motion, which improves the effect of motion style transfer.

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Arangú, Marlene, and Miguel Salido. "A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems." International Journal of Applied Mathematics and Computer Science 21, no. 4 (December 1, 2011): 733–44. http://dx.doi.org/10.2478/v10006-011-0058-2.

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A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems Constraint programming is a powerful software technology for solving numerous real-life problems. Many of these problems can be modeled as Constraint Satisfaction Problems (CSPs) and solved using constraint programming techniques. However, solving a CSP is NP-complete so filtering techniques to reduce the search space are still necessary. Arc-consistency algorithms are widely used to prune the search space. The concept of arc-consistency is bidirectional, i.e., it must be ensured in both directions of the constraint (direct and inverse constraints). Two of the most well-known and frequently used arc-consistency algorithms for filtering CSPs are AC3 and AC4. These algorithms repeatedly carry out revisions and require support checks for identifying and deleting all unsupported values from the domains. Nevertheless, many revisions are ineffective, i.e., they cannot delete any value and consume a lot of checks and time. In this paper, we present AC4-OP, an optimized version of AC4 that manages the binary and non-normalized constraints in only one direction, storing the inverse founded supports for their later evaluation. Thus, it reduces the propagation phase avoiding unnecessary or ineffective checking. The use of AC4-OP reduces the number of constraint checks by 50% while pruning the same search space as AC4. The evaluation section shows the improvement of AC4-OP over AC4, AC6 and AC7 in random and non-normalized instances.

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Osogami, Takayuki, and Tetsuro Morimura. "Time-Consistency of Optimization Problems." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 1945–53. http://dx.doi.org/10.1609/aaai.v26i1.8391.

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We study time-consistency of optimization problems, where we say that an optimization problem is time-consistent if its optimal solution, or the optimal policy for choosing actions, does not depend on when the optimization problem is solved. Time-consistency is a minimal requirement on an optimization problem for the decisions made based on its solution to be rational. We show that the return that we can gain by taking "optimal" actions selected by solving a time-inconsistent optimization problem can be surely dominated by that we could gain by taking "suboptimal" actions. We establish sufficient conditions on the objective function and on the constraints for an optimization problem to be time-consistent. We also show when the sufficient conditions are necessary. Our results are relevant in stochastic settings particularly when the objective function is a risk measure other than expectation or when there is a constraint on a risk measure.

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SHIRZAD, A., and F. LORAN. "GAUGE FIXING IN THE CHAIN-BY-CHAIN METHOD." International Journal of Modern Physics A 17, no. 31 (December 20, 2002): 4801–8. http://dx.doi.org/10.1142/s0217751x0201145x.

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In a recent work7 we showed that for a Hamiltonian system with constraints, the set of constraints can be investigated in the first- and second-class constraint chains. We show here that using this "chain-by-chain" method for an arbitrary system. One can fix the gauges in the most economical and consistent way. We show that it is enough to assume some gauge fixing conditions conjugate to the last elements of first-class chains. The remaining necessary conditions would emerge from consistency conditions.

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Chan, Weng Tat, and Boyd C. Paulson. "Exploratory design using constraints." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 1, no. 1 (February 1987): 59–71. http://dx.doi.org/10.1017/s0890060400000159.

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Engineering design involves the evaluation and satisfaction of a wide variety of constraints. The ability to represent and process these constraints in a computer is important for the verification of the output produced by computer-aided design programs. Constraints need not only check designs but can also be used to derive design solution s that satisfy constraints. The paper discusses how to represent the dual nature of constraints so that design consistency is maintained as the design evolves.Assumptions and rules of thumb are used frequently in design to propose initial solutions. We represent the logic behind the derivation of these assumptions as heuristic procedures and maintain the dependencies between these assumptions and their consequents as an aid to the management of design consistency. We also propose a simple scheme, involving the partitioning of the design modules, to effect design changes when constraint violations occur. An example from structural design illustrates the methodology.

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Wang, Ruiwei, and Roland H. C. Yap. "Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 3850–58. http://dx.doi.org/10.1609/aaai.v36i4.20300.

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Ordered Multi-valued Decision Diagram (MDD) is a compact representation used to model various constraints, such as regular constraints and table constraints. It can be particularly useful for representing ad-hoc problem specific constraints. Many algorithms have been proposed to enforce Generalized Arc Consistency (GAC) on MDD constraints. In this paper, we introduce a new compact representation called Binary Constraint Tree (BCT). We propose tree binary encodings to transform any MDD constraint into a BCT constraint. We also present a specialized algorithm enforcing GAC on the BCT constraint resulting from a MDD constraint. Experimental results on a large set of benchmarks show that the BCT GAC algorithm can significantly outperform state-of-the-art MDD as well as table GAC algorithms.

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GAMBINI, RODOLFO, JERZY LEWANDOWSKI, DONALD MAROLF, and JORGE PULLIN. "ON THE CONSISTENCY OF THE CONSTRAINT ALGEBRA IN SPIN NETWORK QUANTUM GRAVITY." International Journal of Modern Physics D 07, no. 01 (February 1998): 97–109. http://dx.doi.org/10.1142/s0218271898000103.

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We point out several features of the quantum Hamiltonian constraints recently introduced by Thiemann for Euclidean gravity. In particular we discuss the issue of the constraint algebra and of the quantum realization of the object qabVb, which is classically the Poisson Bracket of two Hamiltonians.

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ZHOU, NENG-FA. "Programming finite-domain constraint propagators in Action Rules." Theory and Practice of Logic Programming 6, no. 5 (August 2, 2006): 483–507. http://dx.doi.org/10.1017/s1471068405002590.

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In this paper, we propose a new language, called AR (Action Rules), and describe how various propagators for finite-domain constraints can be implemented in it. An action rule specifies a pattern for agents, an action that the agents can carry out, and an event pattern for events that can activate the agents. AR combines the goal-oriented execution model of logic programming with the event-driven execution model. This hybrid execution model facilitates programming constraint propagators. A propagator for a constraint is an agent that maintains the consistency of the constraint and is activated by the updates of the domain variables in the constraint. AR has a much stronger descriptive power than indexicals, the language widely used in the current finite-domain constraint systems, and is flexible for implementing not only interval-consistency but also arc-consistency algorithms. As examples, we present a weak arc-consistency propagator for the all_distinct constraint and a hybrid algorithm for n-ary linear equality constraints. B-Prolog has been extended to accommodate action rules. Benchmarking shows that B-Prolog as a CLP(FD) system significantly outperforms other CLP(FD) systems.

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Forrest, Jon. "Community rules and speaker behavior: Individual adherence to group constraints on (ING)." Language Variation and Change 27, no. 3 (September 16, 2015): 377–406. http://dx.doi.org/10.1017/s0954394515000137.

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AbstractThis paper investigates the degree to which individual speakers follow the morphosyntactic hierarchy governing grammatical constraints on (ING) in the Southern U.S. city of Raleigh, North Carolina. (ING) was used as the variable of study for its well-studied internal constraints and comparability to previous studies on the internal constraints oft/ddeletion. A lexical category constraint hierarchy for the community was determined via multivariate mixed-effects statistical models, and each speaker's (ING) pattern was compared to this hierarchy. Results show maintenance in grammatical constraints even when taking phonological factors into account, unlike some work ont/ddeletion. Uniformity exists across speakers with respect to the ordering of internal constraints despite the overall decline in rates of –inover time, but constraint weights (expressed as log odds) vary significantly from speaker to speaker, with no correlates to social or internal factors. These results have consequences for representation of individuals in terms of an aggregate pattern, questioning the consistency of factor weight values at the speaker level despite consistent ordering of constraints.

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Lee, Dalgon. "Consistency Dilemma of Korean Energy Policy." Korean Journal of Policy Studies 4 (December 31, 1989): 44–59. http://dx.doi.org/10.52372/kjps04003.

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This paper examines the continuity of Korean energy policy for the last 30 years and consistency of energy policy with other energy-related policies. Because energy policy environment is characterized by high level of uncertainty, long-range planning as well as skillful adaptation to changing environments are both needed. But there are costs the two different approaches must pay. Energy sector has its close connections with economic and environmental sectors. Energy policy-maker should find ways to minimize any conflict between related policies. Economic planning must be designed awaring of the constraints energy sector faces, and energy sector planning inevitably affects environmental quality. And priority among related policy areas must be adjusted according to changing situations. This paper calls policy-makers' attention to consistent policy process in the midst of favorable international energy market and emergence of green movement.

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Zytnicki, M., C. Gaspin, S. De Givry, and T. Schiex. "Bounds Arc Consistency for Weighted CSPs." Journal of Artificial Intelligence Research 35 (July 30, 2009): 593–621. http://dx.doi.org/10.1613/jair.2797.

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The Weighted Constraint Satisfaction Problem (WCSP) framework allows representing and solving problems involving both hard constraints and cost functions. It has been applied to various problems, including resource allocation, bioinformatics, scheduling, etc. To solve such problems, solvers usually rely on branch-and-bound algorithms equipped with local consistency filtering, mostly soft arc consistency. However, these techniques are not well suited to solve problems with very large domains. Motivated by the resolution of an RNA gene localization problem inside large genomic sequences, and in the spirit of bounds consistency for large domains in crisp CSPs, we introduce soft bounds arc consistency, a new weighted local consistency specifically designed for WCSP with very large domains. Compared to soft arc consistency, BAC provides significantly improved time and space asymptotic complexity. In this paper, we show how the semantics of cost functions can be exploited to further improve the time complexity of BAC. We also compare both in theory and in practice the efficiency of BAC on a WCSP with bounds consistency enforced on a crisp CSP using cost variables. On two different real problems modeled as WCSP, including our RNA gene localization problem, we observe that maintaining bounds arc consistency outperforms arc consistency and also improves over bounds consistency enforced on a constraint model with cost variables.

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Vrbsky, Susan V., and Sasa Tomic. "Satisfying temporal consistency constraints of real-time databases." Journal of Systems and Software 45, no. 1 (February 1999): 45–60. http://dx.doi.org/10.1016/s0164-1212(98)10067-5.

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Hertzberg, Mark P. "Constraints on Gravitation from Causality and Quantum Consistency." Advances in High Energy Physics 2018 (November 18, 2018): 1–6. http://dx.doi.org/10.1155/2018/2657325.

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We examine the role of consistency with causality and quantum mechanics in determining the properties of gravitation. We begin by examining two different classes of interacting theories of massless spin 2 particles—gravitons. One involves coupling the graviton with the lowest number of derivatives to matter, the other involves coupling the graviton with higher derivatives to matter, making use of the linearized Riemann tensor. The first class requires an infinite tower of terms for consistency, which is known to lead uniquely to general relativity. The second class only requires a finite number of terms for consistency, which appears as another class of theories of massless spin 2. We recap the causal consistency of general relativity and show how this fails in the second class for the special case of coupling to photons, exploiting related calculations in the literature. In a companion paper Hertzberg and Sandora (2017), this result is generalized to a much broader set of theories. Then, as a causal modification of general relativity, we add light scalar particles and recap the generic violation of universal free-fall they introduce and its quantum resolution. This leads to a discussion of a special type of scalar-tensor theory: the F(R) models. We show that, unlike general relativity, these models do not possess the requisite counterterms to be consistent quantum effective field theories. Together this helps to remove some of the central assumptions made in deriving general relativity.

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Tyson, Christopher J. "Cognitive constraints, contraction consistency, and the satisficing criterion." Journal of Economic Theory 138, no. 1 (January 2008): 51–70. http://dx.doi.org/10.1016/j.jet.2007.01.019.

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Helzerman, R. A., and M. P. Harper. "MUSE CSP: An Extension to the Constraint Satisfaction Problem." Journal of Artificial Intelligence Research 5 (November 1, 1996): 239–88. http://dx.doi.org/10.1613/jair.298.

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This paper describes an extension to the constraint satisfaction problem (CSP) called MUSE CSP (MUltiply SEgmented Constraint Satisfaction Problem). This extension is especially useful for those problems which segment into multiple sets of partially shared variables. Such problems arise naturally in signal processing applications including computer vision, speech processing, and handwriting recognition. For these applications, it is often difficult to segment the data in only one way given the low-level information utilized by the segmentation algorithms. MUSE CSP can be used to compactly represent several similar instances of the constraint satisfaction problem. If multiple instances of a CSP have some common variables which have the same domains and constraints, then they can be combined into a single instance of a MUSE CSP, reducing the work required to apply the constraints. We introduce the concepts of MUSE node consistency, MUSE arc consistency, and MUSE path consistency. We then demonstrate how MUSE CSP can be used to compactly represent lexically ambiguous sentences and the multiple sentence hypotheses that are often generated by speech recognition algorithms so that grammar constraints can be used to provide parses for all syntactically correct sentences. Algorithms for MUSE arc and path consistency are provided. Finally, we discuss how to create a MUSE CSP from a set of CSPs which are labeled to indicate when the same variable is shared by more than a single CSP.

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Long, Zheng-Wen, and Bo Liu. "A New Approach Treating Constrained Systems Based on the Consistency Condition of Constraints." Modern Physics Letters A 18, no. 32 (October 20, 2003): 2273–80. http://dx.doi.org/10.1142/s0217732303012076.

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A new approach treating constrained systems based on the consistency condition of constraints is proposed in this paper. This method is simpler and more rigorous in mathematics. It is not necessary to introduce the concepts of weakly equal, strongly equal, Dirac brackets and Dirac conjecture. The procedure of our method is demonstrated by using Cawley's counterexample to Dirac's conjecture.

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Chabert, Maxime, and Christine Solnon. "A Global Constraint for the Exact Cover Problem: Application to Conceptual Clustering." Journal of Artificial Intelligence Research 67 (March 12, 2020): 509–47. http://dx.doi.org/10.1613/jair.1.11870.

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We introduce the exactCover global constraint dedicated to the exact cover problem, the goal of which is to select subsets such that each element of a given set belongs to exactly one selected subset. This NP-complete problem occurs in many applications, and we more particularly focus on a conceptual clustering application. We introduce three propagation algorithms for exactCover, called Basic, DL, and DL+: Basic ensures the same level of consistency as arc consistency on a classical decomposition of exactCover into binary constraints, without using any specific data structure; DL ensures the same level of consistency as Basic but uses Dancing Links to efficiently maintain the relation between elements and subsets; and DL+ is a stronger propagator which exploits an extra property to filter more values than DL. We also consider the case where the number of selected subsets is constrained to be equal to a given integer variable k, and we show that this may be achieved either by combining exactCover with existing constraints, or by designing a specific propagator that integrates algorithms designed for the NValues constraint. These different propagators are experimentally evaluated on conceptual clustering problems, and they are compared with state-of-the-art declarative approaches. In particular, we show that our global constraint is competitive with recent ILP and CP models for mono-criterion problems, and it has better scale-up properties for multi-criteria problems.

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Benetti, Micol, Salvatore Capozziello, and Gaetano Lambiase. "Updating constraints on f(T) teleparallel cosmology and the consistency with big bang nucleosynthesis." Monthly Notices of the Royal Astronomical Society 500, no. 2 (November 5, 2020): 1795–805. http://dx.doi.org/10.1093/mnras/staa3368.

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ABSTRACT We focus on viable f(T) teleparallel cosmological models, namely power law, exponential, and square-root exponential, carrying out a detailed study of their evolution at all scales. Indeed, these models were extensively analysed in the light of late time measurements, while it is possible to find only upper limits looking at the very early time behaviour, i.e. satisfying the big bang nucleosynthesis (BBN) data on primordial abundance of 4He. Starting from these indications, we perform our analysis considering both background and linear perturbations evolution and constrain, beyond the standard six cosmological parameters, the free parameters of f(T) models in both cases whether the BBN consistency relation is considered or not. We use a combination of Cosmic Microwave Background, Baryon Acoustic Oscillation, Supernovae Ia and galaxy clustering measurements, and find that very narrow constraints on the free parameters of specific f(T) cosmology can be obtained, beyond any previous precision. While no degeneration is found between the helium fraction, YP, and the free parameter of f(T), we note that these models constrain the current Hubble parameter, H0, higher extent than the standard model one, fully compatible with the Riess et al. measurement in the case of power-law f(T) model. Moreover, the free parameters are constrained at non-zero values in more than 3-σ, showing a preference of the observations for extended gravity models.

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Karpenka, N. V., F. Feroz, and M. P. Hobson. "Testing the mutual consistency of different supernovae surveys." Proceedings of the International Astronomical Union 10, S306 (May 2014): 322–25. http://dx.doi.org/10.1017/s1743921314013635.

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AbstractIt is now common practice to constrain cosmological parameters using supernovae (SNe) catalogues constructed from several different surveys. Before performing such a joint analysis, however, one should check that parameter constraints derived from the individual SNe surveys that make up the catalogue are mutually consistent. We describe a statistically-robust mutual consistency test, which we calibrate using simulations, and apply it to each pairwise combination of the surveys making up, respectively, the UNION2 catalogue and the very recent JLA compilation by Betoule et al. We find no inconsistencies in the latter case, but conclusive evidence for inconsistency between some survey pairs in the UNION2 catalogue.

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Song, Yongjia, Marlin W. Ulmer, Barrett W. Thomas, and Stein W. Wallace. "Building Trust in Home Services—Stochastic Team-Orienteering with Consistency Constraints." Transportation Science 54, no. 3 (May 2020): 823–38. http://dx.doi.org/10.1287/trsc.2019.0927.

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In this paper, we consider service applications where drivers serve subscription customers at their homes on a regular basis and at known times. To build trust with customers, the company requires that subscription customers are consistently served by the same driver. In addition to subscription customers, on-demand customers request delivery on a daily basis. For the company, the challenge is to consistently serve the subscription customers while simultaneously maximizing the daily profit from the on-demand customers. We model the problem as a two-stage stochastic decision problem. The first stage determines the assignment of drivers to subscription customers. The second stage is a team-orienteering problem with time windows and mandatory visits by fixed drivers. We present an anticipatory consistent customer assignment policy (ACCA) based on the multiple scenario approach framework. Our computational study shows that ACCA significantly outperforms consistency concepts from the literature, while increasing costs less than 5%.

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Journal articles on the topic 'Consistency constraints'

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