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Constraint Programming on Infinite Data Streams
 PROCEEDINGS OF THE TWENTYSECOND I NTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
"... Classical constraint satisfaction problems (CSPs) are commonly defined on finite domains. In real life, constrained variables can evolve over time. A variable can actually take an infinite sequence of values over discrete time points. In this paper, we propose constraint programming on infinite data ..."
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Classical constraint satisfaction problems (CSPs) are commonly defined on finite domains. In real life, constrained variables can evolve over time. A variable can actually take an infinite sequence of values over discrete time points. In this paper, we propose constraint programming on infinite data streams, which provides a natural way to model constrained timevarying problems. In our framework, variable domains are specified by ωregular languages. We introduce special stream operators as basis to form stream expressions and constraints. Stream CSPs have infinite search space. We propose a search procedure that can recognize and avoid infinite search over duplicate search space. The solution set of a stream CSP can be represented byaBüchi automaton allowing stream values to be nonperiodic. Consistency notions are defined to reduce the search space early. We illustrate the feasibility of the framework by examples and experiments.
A MasterSlave Architecture to Integrate Sets and Finite Domains in Java
"... Abstract. This paper summarizes the lessons learned from the integration of two Java constraint solvers: a set solver (namely JSetL) and a finite domains solver (namely JFD). The most relevant outcome of this experience is the definition of a generic masterslave architecture that can be used to sup ..."
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Abstract. This paper summarizes the lessons learned from the integration of two Java constraint solvers: a set solver (namely JSetL) and a finite domains solver (namely JFD). The most relevant outcome of this experience is the definition of a generic masterslave architecture that can be used to support the cooperation of different solvers. Each slave is responsible for managing constraints of a particular sort and the master, which is also a solver, is in charge of distributing tasks according to a static, apriori policy. This paper first presents this generic architecture in an abstract form; then, its concrete instantiation to the selected case study, i.e., the integration of JSetL and JFD, is also described. This case study was selected because it fully demonstrates the possibilities of this architecture as: (i) the poor performances of JSetL on nonset variables are overwhelmed by the cooperation with JFD; and (ii) the expressive power of JSetL is fully preserved and the integration with JFD demands no restrictions. 1
A Constraint Handling Rules Implementation for KnownArcConsistency in Interactive Constraint Satisfaction Problems
, 2004
"... In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of com ..."
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In classical CLP(FD) systems, domains of variables are completely known at the beginning of the constraint propagation process. However, in systems interacting with an external environment, acquiring the whole domains of variables before the beginning of constraint propagation may cause waste of computation time, or even obsolescence of the acquired data at the time of use.
Constraint Logic Programming
"... Abstract. Constraint Logic Programming (CLP) is one of the most successful branches of Logic Programming; it attracts the interest of theoreticians and practitioners, and it is currently used in many commercial applications. Since the original proposal, it has developed enormously: many languages an ..."
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Abstract. Constraint Logic Programming (CLP) is one of the most successful branches of Logic Programming; it attracts the interest of theoreticians and practitioners, and it is currently used in many commercial applications. Since the original proposal, it has developed enormously: many languages and systems are now available either as open source programs or as commercial systems. Also, CLP has been one of the technologies able to recruit researchers from other communities to the declarative programming cause. Current CLP engines include technologies and results developed in other communities, which themselves discovered logic as an invaluable tool to model and solve reallife problems. 1 The CLP paradigm Constraint Logic Programming (CLP) [7] represents a successful attempt to merge the best features of logic programming (LP) and constraint solving. Constraint solving [127,6,56,31] includes a variety of expressive modelling