Filters








246,554 Hits in 4.5 sec

Effects of Dynamic Variable - Value Ordering Heuristics on the Search Space of Sudoku Modeled as a Constraint Satisfaction Problem

James L. Cox, Stephen Lucci, Tayfun Pay
2019 Inteligencia Artificial  
search effort for some constraint satisfaction problems.  ...  We carry out a detailed analysis of the effects of different dynamic variable and value ordering heuristics on the search space of Sudoku when the encoding method and the filtering algorithm are fixed.  ...  Introduction The manner in which the search space of a problem that has been modeled as a CSP (Constraint Satisfaction Problem) is explored depends on the various techniques that are built into the given  ... 
doi:10.4114/intartif.vol22iss63pp1-15 fatcat:r2pdfg5m7bheji4abrmjy7aepy

Learning and using hyper-heuristics for variable and value ordering in constraint satisfaction problems

Sean A. Bittle, Mark S. Fox
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
This paper explores the use of hyper-heuristics for variable and value ordering in binary Constraint Satisfaction Problems (CSP).  ...  Specifically, we describe the use of a symbolic cognitive architecture, augmented with constraint based reasoning as the hyper-heuristic machine learning framework.  ...  INTRODUCTION In this paper we present a novel approach for learning and using hyper-heuristics to address the problem of variable and value ordering in binary constraint satisfaction problems.  ... 
doi:10.1145/1570256.1570304 dblp:conf/gecco/BittleF09 fatcat:yg2v2faqs5eyfauuexcik6ttym

SOS-Heuristic for Intelligent Exploration of Search Space in CSOP [chapter]

Jaziri Wassim
2008 Tabu Search  
A solution to a constraints satisfaction and optimization problem is an affectation of values to the variables, which improves the objective value while satisfying the constraints.  ...  A satisfaction approach affects values to variables in order to satisfy constraints on these variables.  ... 
doi:10.5772/5597 fatcat:qou6v2x4ojeb3hqhevvzh3kgcm

Stochastic Constraint Programming [article]

Toby Walsh
2009 arXiv   pre-print
They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability.  ...  To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming.  ...  the answer to) the resulting traditional constraint satisfaction problem.  ... 
arXiv:0903.1152v1 fatcat:lyq6id4uefb6lojov435u3jcnm

Research on Two-Stage Fuzzy Programming Model Based on Comprehensive Satisfaction Degree

Zhanjing Wang, Yingjun Li, Fachao Li
2017 ICIC Express Letters  
Then aiming at the fuzzy programming with concrete multi-constraints, we put forward a model of comprehensive satisfaction degree for processing the constraints.  ...  Further, we establish the second model to make final decision. That is the two-stage fuzzy programming model based on comprehensive satisfaction degree (denoted as BCSD-TFPM, for short).  ...  This work is supported by the National Natural Science Foundation of China (71540001, 71371064) and the Natural Science Foundation of Hebei Province (F2015208099, F2015208100).  ... 
doi:10.24507/icicel.11.04.799 fatcat:beyocmjz4fd6xdufacvfsrknkm

Specifying over-constrained problems in default logic [chapter]

Abdul Sattar, Aditya K. Ghose, Randy Goebel
1996 Lecture Notes in Computer Science  
Constraint satisfaction problems for which an assignment of values to all variables which satisfy all available constraints is not possible are referred to as over-constrained problems.  ...  In the previous studies, it has been shown that the classical constraint satisfaction problem (CSP) is deductive in nature, and can be formulated as a classical theorem proving problem [1, 10].  ...  Formally, an over-constrained problem is a constraint satisfaction problem for which there is no assignment of values to all variables such that all the constraints are satisfied.  ... 
doi:10.1007/3-540-61479-6_27 fatcat:rgcehscx2fbdjnnjp3fyr6b5jm

Solving the Weighted Constraint Satisfaction Problems Via the Neural Network Approach

Khalid Haddouch, Karim Elmoutaoukil, Mohamed Ettaouil
2016 International Journal of Interactive Multimedia and Artificial Intelligence  
A wide variety of real world optimization problems can be modelled as Weighted Constraint Satisfaction Problems (WCSPs).  ...  In this paper, we model this problem in terms of in original 0-1 quadratic programming subject to leaner constraints.  ...  New Model of Weighted Constraints Satisfaction Problems A constraint satisfaction problem refers to the problem of finding values to a set of variables, subject to constraints on the acceptable combination  ... 
doi:10.9781/ijimai.2016.4111 fatcat:dxkpejh5wncq3npk7bddfdpf3u

Preventing design conflicts in distributed design systems composed of heterogeneous agents

Baris Canbaz, Bernard Yannou, Pierre-Alain Yvars
2014 Engineering applications of artificial intelligence  
Set-based design and constraint programming techniques are used to explore the overall performance of stochastic design collaborations on a product modeled with uncertainties at a given moment of the design  ...  In our model, design agents can set requirements directly on their wellbeing values that represent how their design targets are likely to be met at a given moment of the design process.  ...  The consistency of the constraint depends on the nature of the initial problem and the earlier constraints defined during progress.  ... 
doi:10.1016/j.engappai.2013.11.017 fatcat:646ubf6mknhs5ambsvx47vdyzu

Taking Advantage of Stable Sets of Variables in Constraint Satisfaction Problems

Eugene C. Freuder, Michael J. Quinn
1985 International Joint Conference on Artificial Intelligence  
Some light is shed on the question of how and when a constraint satisfaction problem can be advantageously divided into subproblems.  ...  Binary constraint satisfaction problems involve finding values for variables subject to constraints between pairs of variables.  ...  ACKNOWLEDGMENTS This paper is based in part upon work supported by the National Science Foundation under Grant MCS 8003307.  ... 
dblp:conf/ijcai/FreuderQ85 fatcat:yykziumzzveslexci4zwmxzftm

Solutions Outlining on the Set of Structured Technological Problems with Imposed Constraints

Vasyl Sheketa, Roman Vovk, Volodymyr Pikh, Yulia Romanyshyn, Kostiantyn Kravtsiv, Liudmyla Poteriailo, Volodymyr Protsiuk, Mykola Pasyeka
2021 Modern Machine Learning Technologies  
A method of estimating technological parameters is introduced, which allows to represent sets of preferences and express their influence on the process of satisfaction and violation of constraints by solving  ...  technological problems.  ...  Value 1 sd corresponds to the level of full satisfaction of the constraints and value 0 sd corresponds to complete violation of the constraint.  ... 
dblp:conf/momlet/SheketaVPRKPPP21 fatcat:4nk27mmy5vgtzduk2s7r67up44

Information Hiding and the Complexity of Constraint Satisfaction [chapter]

Remco C. Veltkamp, Richard H. M. C. Kelleners
1995 Eurographics  
On the one hand, powerful constraint satisfaction is necessarily global, and tends to break information hiding.  ...  On the other hand, preserving strict information hiding increases the complexity of constraint satisfaction, or severely limits the power of the constraint solver.  ...  We call a constraint satisfaction problem node-consistent if and only if for all variables, all values in its domain satisfy the unary constraints on that variable (cf. 15]).  ... 
doi:10.1007/978-3-7091-9457-7_5 fatcat:hwskzf77nnfmtcosellcopmfd4

Page 266 of Behavior Research Methods Vol. 20, Issue 2 [page]

1988 Behavior Research Methods  
It is not the individual hypothesis, however, that is the problem in constraint satisfaction problems.  ...  In particular, suppose that each constraint has an importance value associated with it and that the solution to the problem involves the simultaneous satisfaction of as many of the most important of these  ... 

Fuzzy rrDFCSP and planning

Ian Miguel, Qiang Shen
2003 Artificial Intelligence  
Priorities and preferences are placed on individual constraints and aggregated via fuzzy conjunction to obtain a satisfaction degree for a solution to the problem.  ...  However, the formulation of a static constraint satisfaction problem (CSP) with hard, imperative constraints is insufficient to model many real problems.  ...  The authors thank Peter Jarvis for his assistance in this research and the anonymous referees for their insightful comments which were very useful in revising this paper.  ... 
doi:10.1016/s0004-3702(03)00020-1 fatcat:cko7m5tqh5herc76xjvzmk5l3m

Algorithms for Stochastic CSPs [chapter]

Thanasis Balafoutis, Kostas Stergiou
2006 Lecture Notes in Computer Science  
The Stochastic CSP (SCSP) is a framework recently introduced by Walsh to capture combinatorial decision problems that involve uncertainty and probabilities.  ...  Then we define arc consistency for SCSPs and introduce an arc consistency algorithm that can handle constraints of any arity.  ...  Acknowledgements This work has been supported by GR Pythagoras grant number 1349 under the Operational Program for Education and Initial Training.  ... 
doi:10.1007/11889205_6 fatcat:2hghutuuwrd2rdytwqesefeuv4

Evolving CSP Algorithm in Predicting the Path Loss of Indoor Propagation Models

Anuj Agrawal
2013 International Journal of Computer Applications Technology and Research  
The solution of a constraint satisfaction problem is a set of variable value assignments, which satisfies all members of the set of constraints in the CSP.  ...  The Branch and bound algorithm is used to optimize the constraint satisfaction problem.  ...  Constraint satisfaction deals with the problem defined over finite domain, on the other hand constraint solving algorithm are based on mathematical techniques.  ... 
doi:10.7753/ijcatr0202.1001 fatcat:kagryfvll5dmjervquzqhlq5su
« Previous Showing results 1 — 15 out of 246,554 results