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Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, 1994
In this paper the issue of soft constraint satisfaction is discussed from a fuzzy set theoretical point of view. A fuzzy constraint is considered as a fuzzy relation. Different possible definitions for the degree of joint satisfaction of a set of fuzzy constraints are given, covering other specific soft constraint satisfaction problem (CSP) types such ...
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In this paper the issue of soft constraint satisfaction is discussed from a fuzzy set theoretical point of view. A fuzzy constraint is considered as a fuzzy relation. Different possible definitions for the degree of joint satisfaction of a set of fuzzy constraints are given, covering other specific soft constraint satisfaction problem (CSP) types such ...
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Liquidity management with fuzzy qualitative constraints
Decision Support Systems, 1995Abstract The treasurer of a bank must balance liquidity flows every day in an environment in which some future interest rates and transactions are known precisely, but some are uncertain. Decision support systems based on traditional mathematical programming approach find the optimal plan with respect to precise quantitative constraints provided by ...
Francesco Gardin +2 more
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Agent negotiation as fuzzy constraint processing
2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2003This paper presents a general problem-solving framework for the modeling of agent negotiation via fuzzy constraint processing. In this approach, fuzzy constraint processing serves to improve the agent's individual negotiation strategy, and also to represent the agent negotiation mechanism and interaction framework for multi-objective agent negotiation.
Robert Lai, Menq-Wen Lin
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Fuzzy Constraint Based Answer Validation
2005Answer validation is an important component of any question answering system. In this paper we show how the formalism of prioritized fuzzy constraint satisfaction allows to unify and generalize some common validation strategies. Moreover, answer candidates are represented by fuzzy sets, which allows to handle imprecise answers.
Steven Schockaert +2 more
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Interpretability constraints for fuzzy information granulation
Information Sciences, 2008Information granules are complex entities that arise in the process of abstraction of data and derivation of knowledge. The automatic generation of information granules from data is an important task, since it gives to machines the ability of acquiring knowledge that can be communicated to users.
Corrado Mencar, Anna Maria Fanelli
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A Tractable Subclass of Fuzzy Constraint Networks
2005The Fuzzy Constraint Networks model, a generalization of the Disjunctive Temporal Fuzzy Constraint Networks, is a framework that allows representing and reasoning with fuzzy qualitative and quantitative complex constraints. However, its general complexity is exponential, and we need to find tractable subclasses.
Alfonso Bosch +2 more
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Personalized route problem with fuzzy constraints
2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017The Personalized Route Problem resembles the so-called multi-criteria Shortest Path Problem where every arc (street) of the graph (map) has a set of costs (values) associated to a set of criteria (features). The personalization of the path comes when the user a) determines how important is each criterion according to personal preferences and b ...
Marina Torres +3 more
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Constraint Logic Programming with Fuzzy Sets
1995Constraint Logic Programming language embodying extensional finite Fuzzy Sets is presented. Basic fuzzy set operations (=, ∈, ≠, and ∉) are defined as constraints over fuzzy sets and their elements. Simple list-like representation of sets is presented, with fset/2 as the interpreted set constructor and {} as the empty set. Members of the fuzzy sets are
Ludek Matyska, Hynek Bures
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Closure Operators, Fuzzy Logic and Constraints
1999The notion of closure operator is very useful in several areas of classical mathematics and this suggests to extend it to the framework of fuzzy set theory. In particular, the theory of closure operator gives a powerful tool for (crisp) logics and this since the deduction operator of any monotone logic is a closure operator.
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On Considering Constraints of Different Importance in Fuzzy Constraint Satisfaction Problems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 1998Several real-world applications (e.g., scheduling, configuration, …) can be formulated as Constraint Satisfaction Problems (CSP). In these cases, a set of variables have to be settled to a value with the requirement that they satisfy a set of constraints. Classical CSPs are defined only by means of crisp (Boolean) constraints.
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